Paper Digest: COVID-19 Related Papers (Math, Statistics & Other)
In response to the COVID-19 pandemic, Paper Digest Team extracted all COVID-19 papers on our radar, and generated highlight sentences for them. These results are grouped by topics, and sorted by relevance & date.
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TABLE 1: Paper Digest: COVID-19 Related Papers (Math, Statistics & Other)
| Paper | Author(s) | Source | Date | |
|---|---|---|---|---|
| 1 | Bagging Cross-validated Bandwidth Selection in Nonparametric Regression Estimation with Applications to Large-sized Samples Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To overcome these problems, bagging cross-validation bandwidths are analyzed in this paper. |
D. Barreiro-Ures; R. Cao; M. Francisco-Fernández; | arxiv-stat.ME | 2021-05-10 |
| 2 | Statistical Assessment of Replicability Via Bayesian Model Criticism Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we discuss inference and modeling principles for replicability assessment. |
Yi Zhao; Xiaoquan Wen; | arxiv-stat.ME | 2021-05-09 |
| 3 | The Behavior of Internet Traffic for Internet Services During COVID-19 Pandemic Scenario Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this perspective article, we join from many available studies about the COVID-19 effect at networks and investigate the effects on the Internet traffic of using services such as video streaming, video conferencing, and gaming during 2020’s months of the pandemic. |
Carlos Alexandre Gouvea da Silva; Allan Christian Krainski Ferrari; Cristiano Osinski; Douglas Antonio Firmino Pelacini; | arxiv-eess.SP | 2021-05-09 |
| 4 | Quantification of Pulmonary Involvement in COVID-19 Pneumonia By Means of A Cascade Oftwo U-nets: Training and Assessment on Multipledatasets Using Different Annotation Criteria Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This study aims at exploiting Artificial intelligence (AI) for the identification, segmentation and quantification of COVID-19 pulmonary lesions. |
FRANCESCA LIZZI et. al. | arxiv-eess.IV | 2021-05-06 |
| 5 | Estimating The Design Operating Characteristics in Clinical Trials with The Ordinal Scale Disease Progression Endpoint Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a set of methods for efficient estimation and uncertainty quantification for the design operating characteristics of Bayesian adaptive trials. |
Shirin Golchi; | arxiv-stat.ME | 2021-05-06 |
| 6 | COVID-19 Detection from Chest X-ray Images Using Imprinted Weights Approach Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this challenge, we propose the use of a low-shot learning approach named imprinted weights, taking advantage of the abundance of samples from known illnesses such as pneumonia to improve the detection performance on COVID-19. |
JIANXING ZHANG et. al. | arxiv-eess.IV | 2021-05-04 |
| 7 | COVID-Net CT-S: 3D Convolutional Neural Network Architectures for COVID-19 Severity Assessment Using Chest CT Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Motivated by this challenge, we introduce COVID-Net CT-S, a suite of deep convolutional neural networks for predicting lung disease severity due to COVID-19 infection. |
Hossein Aboutalebi; Saad Abbasi; Mohammad Javad Shafiee; Alexander Wong; | arxiv-eess.IV | 2021-05-04 |
| 8 | Topological Data Analysis of COVID-19 Virus Spike Proteins Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address these current problems, we propose to analyze the birth and death events using lattice paths. |
Moo K. Chung; Hernando Ombao; | arxiv-stat.ML | 2021-05-01 |
| 9 | COVID-Net CXR-S: Deep Convolutional Neural Network for Severity Assessment of COVID-19 Cases from Chest X-ray Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we introduce COVID-Net CXR-S, a convolutional neural network for predicting the airspace severity of a SARS-CoV-2 positive patient based on a CXR image of the patient’s chest. |
HOSSEIN ABOUTALEBI et. al. | arxiv-eess.IV | 2021-05-01 |
| 10 | An Application of Discrete-time SEIR Model to The COVID-19 Spread Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We consider discrete-time SEIR epidemic model in a closed system which does not account for births or deaths, total population size under consideration is constant. |
U. A. Rozikov; S. K. Shoyimardonov; | arxiv-math.DS | 2021-05-01 |
| 11 | Does Covid-19 Mass Testing Work? The Importance of Accounting for The Epidemic Dynamics Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We do so by using an innovative empirical approach which embeds a semi-parametric growth model – where Covid-19 transmission dynamics are allowed to vary across regions and to be impacted by the implementation of the mass testing campaign – into a synthetic control framework which creates an appropriate control group of other Italian regions. |
Davide Ferrari; Steven Stillman; Mirco Tonin; | arxiv-stat.AP | 2021-04-30 |
| 12 | Estimating The Efficiency Gain of Covariate-Adjusted Analyses in Future Clinical Trials Using External Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a general framework for using existing data to estimate the efficiency gain from using a covariate-adjusted estimator of a marginal treatment effect in a future randomized trial. |
Xiudi Li; Sijia Li; Alex Luedtke; | arxiv-stat.ME | 2021-04-30 |
| 13 | A Study on Vaccination Control for COVID-19 in Ireland Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a compartmental model to describe the dynamics of transmission of infection and use it to obtain the optimal vaccination control for the Republic of Ireland. |
Eleni Zavrakli; Andrew Parnell; David Malone; Ken Duffy; Subhrakanti Day; | arxiv-math.OC | 2021-04-30 |
| 14 | Ranking The Information Content of Distance Measures Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a statistical test that can assess the relative information retained when using two different distance measures, and determine if they are equivalent, independent, or if one is more informative than the other. |
Aldo Glielmo; Claudio Zeni; Bingqing Cheng; Gabor Csanyi; Alessandro Laio; | arxiv-stat.ML | 2021-04-30 |
| 15 | An Automated Approach for Timely Diagnosis and Prognosis of Coronavirus Disease Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The proposed approach shows promising results where the classification model achieved 93% accuracy on hold-out data. |
Abbas Raza Ali; Marcin Budka; | arxiv-eess.IV | 2021-04-29 |
| 16 | The Potential Stickiness of Pandemic-induced Behavior Changes in The United States Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present evidence on how much U.S. adults expect their own post-pandemic choices to differ from their pre-pandemic lifestyles in the areas of telecommuting, restaurant patronage, air travel, online shopping, transit use, car commuting, uptake of walking and biking, and home location. |
DEBORAH SALON et. al. | arxiv-stat.AP | 2021-04-29 |
| 17 | Improved Log-Gaussian Approximation for Over-dispersed Poisson Regression: Application to Spatial Analysis of COVID-19 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Provided this, we develop a closed-form inference for an over-dispersed Poisson regression, especially for (over-dispersed) Bayesian Poisson wherein the exact inference is unobtainable. |
Daisuke Murakami; Tomoko Matsui; | arxiv-stat.ME | 2021-04-28 |
| 18 | IATos: AI-powered Pre-screening Tool for COVID-19 from Cough Audio Samples Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: OBJECTIVE: Our objective is to evaluate the possibility of using cough audio recordings (spontaneous or simulated) to detect sound patterns in people who are diagnosed with COVID-19. |
D. Trejo Pizzo; S. Esteban; M. Scetta; | arxiv-eess.AS | 2021-04-27 |
| 19 | Algorithm Is Experiment: Machine Learning, Market Design, and Policy Eligibility Rules Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We use this observation to develop a treatment-effect estimator for a class of stochastic and deterministic algorithms. |
Yusuke Narita; Kohei Yata; | arxiv-econ.EM | 2021-04-26 |
| 20 | FedDPGAN: Federated Differentially Private Generative Adversarial Networks Framework for The Detection of COVID-19 Pneumonia Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Under the FL framework and Differentially Private thinking, we propose a FederatedDifferentially Private Generative Adversarial Network (FedDPGAN) to detectCOVID-19 pneumonia for sustainable smart cities. |
LONGLING ZHANG et. al. | arxiv-eess.IV | 2021-04-26 |
| 21 | Mean Field Control Problems for Vaccine Distribution Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we build a mean-field variational problem in a spatial domain, which controls the propagation of pandemic by the optimal transportation strategy of vaccine distribution. |
Wonjun Lee; Siting Liu; Wuchen Li; Stanley Osher; | arxiv-math.OC | 2021-04-24 |
| 22 | Automatic Diagnosis of COVID-19 from CT Images Using CycleGAN and Transfer Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, a method based on pre-trained deep neural networks is presented, which, by taking advantage of a cyclic generative adversarial net (CycleGAN) model for data augmentation, has reached state-of-the-art performance for the task at hand, i.e., 99.60% accuracy. |
NAVID GHASSEMI et. al. | arxiv-eess.IV | 2021-04-24 |
| 23 | Asymptotic Incidence Rate Estimation of SARS-COVID-19 Via A Polya Process Scheme: A Comparative Analysis in Italy and European Countries Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In the Polya framework, we provide both the distribution of infected cases and the asymptotic estimation of the incidence rate, showing that data are consistent with a general underlying process at different scales. |
Filippo Carone Fabiani; | arxiv-stat.ME | 2021-04-23 |
| 24 | Data Filtering Methods for SARS-CoV-2 Wastewater Surveillance Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we investigate 13 smoothing algorithms applied to the virus signals monitored in four wastewater treatment plants in Austria. |
REZGAR ARABZADEH et. al. | arxiv-stat.AP | 2021-04-23 |
| 25 | A Probabilistic Assessment of The COVID-19 Lockdown on Air Quality in The UK Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we use 550,134 NO2 data points from 237 stations in the UK to build a spatiotemporal Gaussian process capable of predicting NO2 levels across the entire UK. |
Thomas Pinder; Michael Hollaway; Christopher Nemeth; Paul J. Young; David Leslie; | arxiv-stat.AP | 2021-04-22 |
| 26 | Assessing The Effectiveness of Regional Physical Distancing Measures of COVID-19 in Rural Regions of British Columbia Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Building on the Bayesian epidemiological model of Anderson et al. (2020), we propose a hierarchical Bayesian model with time-varying regional parameters to account for the relative reduction in contact due to physical distancing and increased testing from March to December of 2020. |
Geoffrey McGregor; Jennifer Tippett; Andy T. S. Wan; Mengxiao Wang; Samuel W. K. Wong; | arxiv-stat.AP | 2021-04-22 |
| 27 | Impact of COVID-19 on Travel Behaviour, Transport, Lifestyles and Location Choices in Scotland Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: As part of the analysis, statistical models were developed to provide an insight into both the relationships between the levels of non compliance with COVID-19 regulations and demographic variables and the respondent attributes which might affect future public transport usage. |
Lucy Downey; Achille Fonzone; Grigorios Fountas; Torren Semple; | arxiv-stat.AP | 2021-04-21 |
| 28 | Auto-FedAvg: Learnable Federated Averaging for Multi-Institutional Medical Image Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we design a new data-driven approach, namely Auto-FedAvg, where aggregation weights are dynamically adjusted, depending on data distributions across data silos and the current training progress of the models. |
YINGDA XIA et. al. | arxiv-eess.IV | 2021-04-20 |
| 29 | Fitbeat: COVID-19 Estimation Based on Wristband Heart Rate Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The presence of COVID-19 in the cohort in this work was either confirmed through a positive swab test, or inferred through the self-reporting of a combination of symptoms including fever, respiratory symptoms, loss of smell or taste, tiredness and gastrointestinal symptoms. |
SHUO LIU et. al. | arxiv-eess.SP | 2021-04-19 |
| 30 | Domain Adaptation Based Self-correction Model for COVID-19 Infection Segmentation in CT Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, we propose a prior knowledge driven domain adaptation and a dual-domain enhanced self-correction learning scheme. |
QIANGGUO JIN et. al. | arxiv-eess.IV | 2021-04-19 |
| 31 | A Black-Scholes User’s Guide to The Bachelier Model Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This study reviews the literature on Bachelier’s pioneering option pricing model and summarizes the practical results on volatility conversion, risk management, stochastic volatility, and barrier options pricing to facilitate the model transition. |
Jaehyuk Choi; Minsuk Kwak; Chyng Wen Tee; Yumeng Wang; | arxiv-q-fin.MF | 2021-04-17 |
| 32 | SIRSi-Vaccine Dynamical Model for Covid-19 Pandemic Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work a Susceptible – Infected – Removed – Sick with vaccination (SIRSi-Vaccine) model is proposed. |
Cristiane M. Batistela; Diego P. F. Correa; Átila M Bueno; José R. C. Piqueira; | arxiv-math.DS | 2021-04-15 |
| 33 | Bayesian Synthetic Likelihood Estimation for Underreported Non-Stationary Time Series: Covid-19 Incidence in Spain Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we explore the performance of Bayesian Synthetic Likelihood to estimate the parameters of a model capable of dealing with misreported information and to reconstruct the most likely evolution of the phenomenon. |
David Moriña; Amanda Fernández-Fontelo; Alejandra Cabaña; Argimiro Arratia; Pedro Puig; | arxiv-stat.ME | 2021-04-15 |
| 34 | Data-driven Optimization Model for Global Covid-19 Intervention Plans Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we describe an integer programming approach to prescribe intervention plans that optimizes for both the minimal number of daily new cases and economic impact. |
Chang Liu; Akshay Budhkar; | arxiv-math.OC | 2021-04-15 |
| 35 | Vision Transformer Using Low-level Chest X-ray Feature Corpus for COVID-19 Diagnosis and Severity Quantification Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this problem, here we propose a novel Vision Transformer that utilizes low-level CXR feature corpus obtained from a backbone network that extracts common CXR findings. |
SANGJOON PARK et. al. | arxiv-eess.IV | 2021-04-15 |
| 36 | Deep Learning for COVID-19 Diagnosis Based Feature Selection Using Binary Differential Evolution Algorithm Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, in this paper a hybrid approach based on a deep network is presented. |
Mohammad Saber Iraji; Mohammad-Reza Feizi-Derakhshi; Jafar Tanha; | arxiv-eess.IV | 2021-04-15 |
| 37 | COVID-19 Clinical Footprint to Infer About Mortality Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: Information of 1.6 million patients identified as SARS-CoV-2 positive in Mexico is used to understand the relationship between comorbidities, symptoms, hospitalizations and deaths … |
Carlos E. Rodríguez; Ramsés H. Mena; | arxiv-stat.AP | 2021-04-14 |
| 38 | A Review and Evaluation of Secondary School Accountability in England: Statistical Strengths, Weaknesses, and Challenges for ‘Progress 8’ Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: School performance measures are published annually in England to hold schools to account and to support parental school choice. This article reviews and evaluates the Progress 8 … |
Lucy Prior; John Jerrim; Dave Thomson; George Leckie; | arxiv-stat.AP | 2021-04-13 |
| 39 | COVID-19 Case Data for Italy Stratified By Age Class Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The dataset described in this paper contains daily data about COVID-19 cases that occurred in Italy over the period from Jan. 28, 2020 to March 20, 2021, divided into ten age classes of the population, the first class being 0-9 years, the tenth class being 90 years and over. |
Giuseppe Calafiore; Giulia Fracastoro; | arxiv-stat.ML | 2021-04-13 |
| 40 | Increased Risk of Hospitalisation for COVID-19 Patients Infected with SARS-CoV-2 Variant B.1.1.7 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: OBJECTIVE: To evaluate the association between coronavirus disease 2019 (COVID-19) diagnosis with SARS-CoV-2 variant B.1.1.7 (also known as Variant of Concern 202012/01) and the … |
TOMMY NYBERG et. al. | arxiv-stat.AP | 2021-04-12 |
| 41 | Oil-US Stock Market Nexus: Some Insights About The New Coronavirus Crisis Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we use a wavelet approach and daily data from February 18, 2020 to August 15, 2020. |
Claudiu Albulescu; Michel Mina; Cornel Oros; | arxiv-q-fin.CP | 2021-04-12 |
| 42 | A Smoothed and Probabilistic PARAFAC Model with Covariates Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a smoothed probabilistic PARAFAC model with covariates (SPACO) to tackle these two problems while utilizing auxiliary covariates of interest. |
Leying Guan; | arxiv-stat.ME | 2021-04-11 |
| 43 | Detecting COVID-19 and Community Acquired Pneumonia Using Chest CT Scan Images with Deep Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a two-stage Convolutional Neural Network (CNN) based classification framework for detecting COVID-19 and Community-Acquired Pneumonia (CAP) using the chest Computed Tomography (CT) scan images. |
SHUBHAM CHAUDHARY et. al. | arxiv-eess.IV | 2021-04-11 |
| 44 | Routine Hospital-based SARS-CoV-2 Testing Outperforms State-based Data in Predicting Clinical Burden Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present here an approach under multilevel regression and poststratification (MRP) to collecting and analyzing data on viral exposure among patients in a hospital system and performing statistical adjustment that has been made publicly available to estimate true viral incidence and trends in the community. |
Len Covello; Andrew Gelman; Yajuan Si; Siquan Wang; | arxiv-stat.AP | 2021-04-09 |
| 45 | Inferring Risks of Coronavirus Transmission from Community Household Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here, we perform exploratory, residual-based, and transmission-dynamic household analysis of the Office for National Statistics (ONS) COVID-19 Infection Survey (CIS) data from 26 April 2020 to 8 March 2021 in England. |
THOMAS HOUSE et. al. | arxiv-stat.AP | 2021-04-09 |
| 46 | Fractional Model for CoViD-19 Dynamics Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper is proposed a non-integer order model to describe the dynamics of CoViD-19 in a standard population. |
João P. S. Maurício de Carvalho; Beatriz Moreira-Pinto; | arxiv-math.DS | 2021-04-09 |
| 47 | A Hierarchical Bayesian Model for Stochastic Spatiotemporal SIR Modeling and Prediction of COVID-19 Cases and Hospitalizations Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Most COVID-19 predictive modeling efforts use statistical or mathematical models to predict national- and state-level COVID-19 cases or deaths in the future. |
CURTIS B. STORLIE et. al. | arxiv-stat.AP | 2021-04-08 |
| 48 | DenResCov-19: A Deep Transfer Learning Network for Robust Automatic Classification of COVID-19, Pneumonia, and Tuberculosis from X-rays Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this regard, the objective of this work is to develop a new deep transfer learning pipeline to diagnose patients with COVID-19, pneumonia, and tuberculosis, based on chest x-ray images. |
MICHAIL MAMALAKIS et. al. | arxiv-eess.IV | 2021-04-08 |
| 49 | Dual-Consistency Semi-Supervised Learning with Uncertainty Quantification for COVID-19 Lesion Segmentation from CT Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Specifically, we present a dual-consistency learning scheme that simultaneously imposes image transformation equivalence and feature perturbation invariance to effectively harness the knowledge from unlabeled data. |
Yanwen Li; Luyang Luo; Huangjing Lin; Hao Chen; Pheng-Ann Heng; | arxiv-eess.IV | 2021-04-07 |
| 50 | Information Bottleneck Attribution for Visual Explanations of Diagnosis and Prognosis Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we introduce a robust visual explanation method to address this problem for medical applications. |
UGUR DEMIR et. al. | arxiv-eess.IV | 2021-04-06 |
| 51 | TB-Net: A Tailored, Self-Attention Deep Convolutional Neural Network Design for Detection of Tuberculosis Cases from Chest X-ray Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Motivated by this pressing need and the recent recommendation by the World Health Organization (WHO) for the use of computer-aided diagnosis of TB, we introduce TB-Net, a self-attention deep convolutional neural network tailored for TB case screening. |
Alexander Wong; James Ren Hou Lee; Hadi Rahmat-Khah; Ali Sabri; Amer Alaref; | arxiv-eess.IV | 2021-04-06 |
| 52 | Insight About Detection, Prediction and Weather Impact of Coronavirus (Covid-19) Using Neural Network Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we tried to detect Covid-19 by classification of Covid-19, pneumonia and normal chest X-Rays. |
A K M Bahalul Haque; Tahmid Hasan Pranto; Abdulla All Noman; Atik Mahmood; | arxiv-eess.IV | 2021-04-05 |
| 53 | In-Line Image Transformations for Imbalanced, Multiclass Computer Vision Classification of Lung Chest X-Rays Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Deep learning techniques such as convolutional neural networks (CNNs) are able to select features that distinguish between healthy and disease states for other lung pathologies; this study aims to leverage that body of literature in order to apply image transformations that would serve to balance the lack of COVID-19 LCXR data. |
Alexandrea K. Ramnarine; | arxiv-eess.IV | 2021-04-05 |
| 54 | A Generalized Unscented Transformation for Probability Distributions Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we develop the generalized unscented transform (GenUT), which uses adaptable sigma points that can be positively constrained, and accurately approximates the mean, covariance, and skewness of an independent random vector of most probability distributions, while being able to partially approximate the kurtosis. |
DONALD EBEIGBE et. al. | arxiv-stat.ME | 2021-04-05 |
| 55 | Automated Lung Segmentation from CT Images of Normal and COVID-19 Pneumonia Patients Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This study investigates the performance of a deep learning-based model for lung segmentation from CT images for normal and COVID-19 patients. |
FAEZE GHOLAMIANKHAH et. al. | arxiv-eess.IV | 2021-04-05 |
| 56 | Multi-Feature Semi-Supervised Learning for COVID-19 Diagnosis from Chest X-ray Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To provide a solution to this, in this work, we propose a semi-supervised learning (SSL) approach using minimal data for training. |
Xiao Qi; John L. Nosher; David J. Foran; Ilker Hacihaliloglu; | arxiv-eess.IV | 2021-04-04 |
| 57 | A COVINDEX Based on A GAM Beta Regression Model with An Application to The COVID-19 Pandemic in Italy Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper a near real-time COVINDEX is proposed for monitoring the evolution of the pandemic. |
Luca Scrucca; | arxiv-stat.AP | 2021-04-03 |
| 58 | Detection of COVID-19 Disease Using Deep Neural Networks with Ultrasound Imaging Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a work in progress that proposes the analysis of images of lung ultrasound scans using a convolutional neural network. |
Carlos Rojas-Azabache; Karen Vilca-Janampa; Renzo Guerrero-Huayta; Dennis Núñez-Fernández; | arxiv-eess.IV | 2021-04-03 |
| 59 | Weekly Bayesian Modelling Strategy to Predict Deaths By COVID-19: A Model and Case Study for The State of Santa Catarina, Brazil Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here we propose changes to extend the model and improve its forecasting capabilities. |
Pedro Henrique da Costa Avelar; Luis C. Lamb; Sophia Tsoka; Jonathan Cardoso-Silva; | arxiv-stat.AP | 2021-04-02 |
| 60 | Dynamic Silos: Modularity in Intra-organizational Communication Networks During The Covid-19 Pandemic Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We analyze aggregated, anonymized metadata from over 360 billion emails within over 4000 organizations worldwide to examine changes in network community structures from 2019 through 2020. |
JONATHAN LARSON et. al. | arxiv-stat.ML | 2021-04-01 |
| 61 | Explaining COVID-19 and Thoracic Pathology Model Predictions By Identifying Informative Input Features Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose Inverse IBA to identify all informative regions. |
ASHKAN KHAKZAR et. al. | arxiv-eess.IV | 2021-04-01 |
| 62 | Rapid Quantification of COVID-19 Pneumonia Burden from Computed Tomography with Convolutional LSTM Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a new fully automated deep learning framework for rapid quantification and differentiation between lung lesions in COVID-19 pneumonia from both contrast and non-contrast CT images using convolutional Long Short-Term Memory (ConvLSTM) networks. |
KAJETAN GRODECKI et. al. | arxiv-eess.IV | 2021-03-31 |
| 63 | Mobility Functional Areas and COVID-19 Spread Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work introduces a new concept of functional areas called Mobility Functional Areas (MFAs), i.e., the geographic zones highly interconnected according to the analysis of mobile positioning data. |
STEFANO MARIA IACUS et. al. | arxiv-stat.AP | 2021-03-31 |
| 64 | Virus Infections, Corona Surfaces, and Extra Components in The Moduli Space of Stable Surfaces Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We construct examples of non-smoothable stable surfaces, that we call Corona surfaces, with invariants in a wide range comprising all possible invariants of smooth minimal surfaces of general type but non-standard second plurigenus. |
Sönke Rollenske; | arxiv-math.AG | 2021-03-31 |
| 65 | Selection of An Engineering Institution: Students Perceptions of Choice Characteristics and Suitability Under The COVID-19 Pandemic Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The purpose of this study is to critically examine choice characteristics that affect students choice for EI and consequently to explore relationships between institutional characteristics and the suitability of EI during the COVID19 pandemic across students characteristics. |
Prashant Mahajan; | arxiv-stat.AP | 2021-03-30 |
| 66 | A Database of Travel-related Behaviors and Attitudes Before, During, and After COVID-19 in The United States Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To capture some of these impacts in the United States, we are conducting a nationwide longitudinal survey collecting information about travel-related behaviors and attitudes before, during, and after the COVID-19 pandemic. |
RISHABH SINGH CHAUHAN et. al. | arxiv-stat.AP | 2021-03-29 |
| 67 | Data Integration Through Outcome Adaptive LASSO and A Collaborative Propensity Score Approach Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Several estimation approaches have been proposed recently using an auxiliary probability sample which provides representative covariate information of the target population. In the context of efficient and doubly robust estimation approaches for estimating a population mean, we develop two data adaptive methods for variable selection using the outcome adaptive LASSO and a collaborative propensity score, respectively. |
Asma Bahamyirou; Mireille E. Schnitzer; | arxiv-stat.ME | 2021-03-28 |
| 68 | Mixing-AdaSIN: Constructing A De-biased Dataset Using Adaptive Structural Instance Normalization and Texture Mixing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose Mixing-AdaSIN; a bias mitigation method that uses a generative model to generate de-biased images by mixing texture information between different labeled CT scans with semantically similar features. To demonstrate the efficacy of our method, we construct a biased COVID-19 vs. bacterial pneumonia dataset based on CT protocols and compare with existing state-of-the-art de-biasing methods. |
MYEONGKYUN KANG et. al. | arxiv-eess.IV | 2021-03-26 |
| 69 | Explainability Guided Multi-Site COVID-19 CT Classification Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we overcome three challenges in the automation of this process: (i) the limited number of supervised positive cases, (ii) the lack of region-based supervision, and (iii) the variability across acquisition sites. |
Ameen Ali; Tal Shaharabany; Lior Wolf; | arxiv-eess.IV | 2021-03-25 |
| 70 | Deep Learning with Robustness to Missing Data: A Novel Approach to The Detection of COVID-19 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In the context of the current global pandemic and the limitations of the RT-PCR test, we propose a novel deep learning architecture, DFCN, (Denoising Fully Connected Network) for the detection of COVID-19 using laboratory tests and chest x-rays. |
ERDI ÇALLI et. al. | arxiv-eess.IV | 2021-03-25 |
| 71 | A Queueing-Theoretic Framework for Evaluating Transmission Risks in Service Facilities During A Pandemic Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a new modeling framework for evaluating the risk of disease transmission during a pandemic in small-scale settings driven by stochasticity in the arrival and service processes, i.e., congestion-prone confined-space service facilities, such as grocery stores. |
Kang Kang; Sherwin Doroudi; Mohammad Delasay; Alexander Wickeham; | arxiv-math.PR | 2021-03-24 |
| 72 | Investigating The Relationship Between Air Quality and COVID-19 Transmission Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We used data from 23 provinces in Italy to build a generalized additive model to investigate the association between the effective reproductive number of the disease and air quality while controlling for ambient environmental variables and changes in human mobility. |
Laura Albrecht; Paulina Czarnecki; Bennet Sakelaris; | arxiv-stat.AP | 2021-03-24 |
| 73 | Consistency Between Household and County Measures of K-12 Onsite Schooling During The COVID-19 Pandemic Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper investigates school operational status data sources during the COVID-19 pandemic, comparing self-report data collected nationally on the household level through a Facebook-based survey with data collected at district and county levels throughout the country. |
CARLY LUPTON-SMITH et. al. | arxiv-stat.AP | 2021-03-24 |
| 74 | Bayesian Imputation of COVID-19 Positive Test Counts for Nowcasting Under Reporting Lag Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We adopt a Bayesian approach that provides for subjective priors on parameters and a hierarchical structure for an underlying latent intensity process for the infection counts. |
RADKA JERSAKOVA et. al. | arxiv-stat.AP | 2021-03-23 |
| 75 | Dynamic Characterization of Control SIR-type Systems and Optimal Single-interval Control Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The objective of this work is to provide a full dynamic characterization of SIR-type systems under single-interval control actions and, based on it, to find the control action that produces the smallest number of infected individuals at the end of the epidemic that avoids second wave outbreaks. |
A. H. González; A. L. Anderson; A. Ferramosca; E. A. Hernandez-Vargas; | arxiv-math.OC | 2021-03-20 |
| 76 | Comments on Factors Associated with The Spatial Heterogeneity of The First Wave of COVID-19 in France: A Nationwide Geo-epidemiological Study By Gaudart Et Al Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We make some critical comments on their work which may be useful for future, similar studies. |
José A. Ferreira; | arxiv-stat.AP | 2021-03-19 |
| 77 | Predicting Covid-19 EMS Incidents from Daily Hospitalization Trends Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Introduction: The aim of our retrospective study was to quantify the impact of Covid-19 on the spatiotemporal distribution of Emergency Medical Services (EMS) demands in Travis County, Austin, Texas and propose a robust model to forecast Covid-19 EMS incidents in the short term to improve EMS performance. |
Ngoc Mai Tran; Evdokia Nikolova; David Kulpanowski; Yangxinyu Xie; Joshua Ong; | arxiv-stat.AP | 2021-03-19 |
| 78 | A Probabilistic State Space Model for Joint Inference from Differential Equations and Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We here show that this allows such methods to be combined very directly, with conceptual and numerical ease, with latent force models in the ODE itself. |
Jonathan Schmidt; Nicholas Krämer; Philipp Hennig; | arxiv-stat.ML | 2021-03-18 |
| 79 | Conformalized Survival Analysis Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we develop an inferential method based on ideas from conformal prediction, which can wrap around any survival prediction algorithm to produce calibrated, covariate-dependent lower predictive bounds on survival times. |
Emmanuel J. Candès; Lihua Lei; Zhimei Ren; | arxiv-stat.ME | 2021-03-17 |
| 80 | COVIDx-US — An Open-access Benchmark Dataset of Ultrasound Imaging Data for AI-driven COVID-19 Analytics Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Motivated by these attributes and the promise of artificial intelligence tools to aid clinicians, we introduce COVIDx-US, an open-access benchmark dataset of COVID-19 related ultrasound imaging data. |
ASHKAN EBADI et. al. | arxiv-eess.IV | 2021-03-17 |
| 81 | Identification and Prediction of Time-varying Parameters of COVID-19 Model: A Data-driven Deep Learning Approach Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, a variant of physics-informed neural network (PINN) is adopted to identify the time-varying parameters of the Susceptible-Infectious-Recovered-Deceased model for the spread of COVID-19 by fitting daily reported cases. |
Jie Long; Abdul Khaliq; Khaled Furati; | arxiv-math.DS | 2021-03-17 |
| 82 | Immune Response in SARS-CoV-2 Epidemics: A Fractional-order Model Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we propose a non-integer order model to understand the dynamics of cytotoxic T lymphocytes in the presence of SARS-CoV-2. |
João Paulo Simões Maurício de Carvalho; | arxiv-math.DS | 2021-03-16 |
| 83 | DiCOVA Challenge: Dataset, Task, and Baseline System for COVID-19 Diagnosis Using Acoustics Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce the challenge and provide a detailed description of the task, and present a baseline system for the task. |
ANANYA MUGULI et. al. | arxiv-eess.AS | 2021-03-16 |
| 84 | The Role of Mobility and Sanitary Measures on Covid-19 in Costa Rica, March Through July 2020 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The aim of this paper is to infer the effects that changes on human mobility had on the transmission dynamics during the first four months of the SARS-CoV-2 outbreak in Costa Rica, before community transmission was established in the country. |
LUIS A. BARBOZA et. al. | arxiv-stat.AP | 2021-03-15 |
| 85 | Identification of COVID-19 Mortality Patterns in Brazil By A Functional QR Decomposition Analysis Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper introduces a functional extension of the QR decomposition of linear algebra and shows its application to identify independent patterns (curves) of COVID-19 mortality in Brazil’s states. |
Jorge C. Lucero; | arxiv-stat.AP | 2021-03-15 |
| 86 | Effect of Social Isolation in Dengue Cases in The State of Sao Paulo, Brazil: An Analysis During The COVID-19 Pandemic Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our objective was to evaluate the effect of reduced mobility due to this pandemic in the occurrence of dengue in the state of S\~ao Paulo, Brazil. |
GLEICE MARGARETE DE SOUZA CONCEIÇÃO et. al. | arxiv-stat.AP | 2021-03-15 |
| 87 | Estimation of Parameters of The Gumbel Type-II Distribution Under AT-II PHCS with An Application of Covid-19 Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we investigate the classical and Bayesian estimation of unknown parameters of the Gumbel type-II distribution based on adaptive type-II progressive hybrid censored sample (AT-II PHCS). |
Subhankar Dutta; Suchandan Kayal; | arxiv-stat.ME | 2021-03-15 |
| 88 | Long-term Regulation of Prolonged Epidemic Outbreaks in Large Populations Via Adaptive Control: A Singular Perturbation Approach Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper approaches NPI tuning as a control-theoretic problem, starting from a simple dynamic model for social distancing based on the classical SIR epidemics model. |
M. Ali Al-Radhawi; Mahdiar Sadeghi; Eduardo D. Sontag; | arxiv-math.OC | 2021-03-15 |
| 89 | COVID-19 Infection Localization and Severity Grading from Chest X-ray Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Numerous studies have proposed Deep Learning approaches for the automatic diagnosis of COVID-19. To accomplish this, we have constructed the largest benchmark dataset with 33,920 CXR images, including 11,956 COVID-19 samples, where the annotation of ground-truth lung segmentation masks is performed on CXRs by a novel human-machine collaborative approach. |
ANAS M. TAHIR et. al. | arxiv-eess.IV | 2021-03-14 |
| 90 | Longitudinal Quantitative Assessment of COVID-19 Infection Progression from Chest CTs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a new framework to identify infection at a voxel level (identification of healthy lung, consolidation, and ground-glass opacity) and visualize the progression of COVID-19 using sequential low-dose non-contrast CT scans. |
SEONG TAE KIM et. al. | arxiv-eess.IV | 2021-03-12 |
| 91 | Vision Transformer for COVID-19 CXR Diagnosis Using Chest X-ray Feature Corpus Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To mitigate this problem, we propose a novel vision Transformer by using the low-level CXR feature corpus that are obtained to extract the abnormal CXR features. |
SANGJOON PARK et. al. | arxiv-eess.IV | 2021-03-11 |
| 92 | Parametric Quantile Regression Models for Fitting Double Bounded Response with Application to COVID-19 Mortality Rate Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we develop two fully parametric quantile regression models, based on power Johnson SB distribution Cancho et al. (2020), for modeling unit interval response at different quantiles. |
Diego I. Gallardo; Marcelo Bourguignon; Yolanda M. Gómez; Christian Caamaño-Carrillo; | arxiv-stat.ME | 2021-03-11 |
| 93 | Severity Quantification and Lesion Localization of COVID-19 on CXR Using Vision Transformer Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Several groups proposed deep learning algorithms that quantify the severity of COVID-19 using the array-based COVID-19 labels and localize the lesions with explainability maps. |
GWANGHYUN KIM et. al. | arxiv-eess.IV | 2021-03-11 |
| 94 | Bayesian Sequential Data Assimilation for COVID-19 Forecasting Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a Bayesian sequential data assimilation method for COVID-19 forecasting. |
Maria L. Daza-Torres; Marcos A. Capistrán; Antonio Capella; J. Andrés Christen; | arxiv-stat.AP | 2021-03-10 |
| 95 | Quadruple Augmented Pyramid Network for Multi-class COVID-19 Segmentation Via CT Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, a multi-class COVID-19 CT segmentation is proposed aiming at helping radiologists estimate the extent of effected lung volume. |
Ziyang Wang; | arxiv-eess.IV | 2021-03-09 |
| 96 | Generalizable Limited-Angle CT Reconstruction Via Sinogram Extrapolation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Hereby we propose ExtraPolationNetwork for limited-angle CT reconstruction via the introduction of a sinogram extrapolation module, which is theoretically justified. |
CE WANG et. al. | arxiv-eess.IV | 2021-03-09 |
| 97 | CovidGAN: Data Augmentation Using Auxiliary Classifier GAN for Improved Covid-19 Detection Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, in this research, we present a method to generate synthetic chest X-ray (CXR) images by developing an Auxiliary Classifier Generative Adversarial Network (ACGAN) based model called CovidGAN. |
ABDUL WAHEED et. al. | arxiv-eess.IV | 2021-03-08 |
| 98 | Forest Guided Smoothing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We use the output of a random forest to define a family of local smoothers with spatially adaptive bandwidth matrices. |
Isabella Verdinelli; Larry Wasserman; | arxiv-stat.ML | 2021-03-08 |
| 99 | A Review of Spatiotemporal Models for Count Data in R Packages. A Case Study of COVID-19 Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The main objective of this paper is to present a review describing the most important approaches that can be used to model and analyse count data when questions of scientific interest concern both their spatial and their temporal behaviour and we monitor their performance under the same data set. |
María Victoria Ibáñez; Marina Martínez-Garcia; Amelia Simó; | arxiv-stat.AP | 2021-03-08 |
| 100 | Trends in Risks of Severe Events and Lengths of Stay for COVID-19 Hospitalisations in England Over The Pre-vaccination Era: Results from The Public Health England SARI-Watch Surveillance Scheme Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We applied parametric multi-state mixture models, accounting for censored outcomes and regressing risks and times between events on month of admission, geography, and baseline characteristics. |
PETER D. KIRWAN et. al. | arxiv-stat.AP | 2021-03-08 |
| 101 | Estimating Intervention Effects on Infectious Disease Control: The Effect of Community Mobility Reduction on Coronavirus Spread Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a spatiotemporal model that estimates the causal effect of changes in community mobility (intervention) on infection rates. |
ANDREW GIFFIN et. al. | arxiv-stat.ME | 2021-03-07 |
| 102 | Graph-based Pyramid Global Context Reasoning with A Saliency-aware Projection for COVID-19 Lung Infections Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle these issues, we propose a Graph-based Pyramid Global Context Reasoning (Graph-PGCR) module, which is capable of modeling long-range dependencies among disjoint infections as well as adapt size variation. |
HUIMIN HUANG et. al. | arxiv-eess.IV | 2021-03-06 |
| 103 | Resource Distribution Under Spatiotemporal Uncertainty of Disease Spread: Stochastic Versus Robust Approaches Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we develop mathematical frameworks for optimizing locations of distribution centers and plans for distributing resources such as test kits and vaccines under spatiotemporal uncertainties of infection and demand trends. |
Beste Basciftci; Xian Yu; Siqian Shen; | arxiv-math.OC | 2021-03-06 |
| 104 | DOPE: D-Optimal Pooling Experimental Design with Application for SARS-CoV-2 Screening Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a novel pooling strategy that implements D-Optimal Pooling Experimental design (DOPE). |
Yair Daon; Amit Huppert; Uri Obolski; | arxiv-stat.AP | 2021-03-05 |
| 105 | Self-supervised Deep Convolutional Neural Network for Chest X-ray Classification Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a self-supervised deep neural network that is pretrained on an unlabeled chest X-ray dataset. |
Matej Gazda; Jakub Gazda; Jan Plavka; Peter Drotar; | arxiv-eess.IV | 2021-03-04 |
| 106 | A Two-Sample Robust Bayesian Mendelian Randomization Method Accounting for Linkage Disequilibrium and Idiosyncratic Pleiotropy with Applications to The COVID-19 Outcome Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To resolve those two issues, we propose a novel Robust Bayesian Mendelian Randomization (RBMR) model that uses the more robust multivariate generalized t-distribution to model such direct effects in a probabilistic model framework which can also incorporate the LD structure explicitly. |
Anqi Wang; Zhonghua Liu; | arxiv-stat.ME | 2021-03-04 |
| 107 | Probabilistic Combination of Eigenlungs-based Classifiers for COVID-19 Diagnosis in Chest CT Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose an ensemble classifier based on probabilistic Support Vector Machine (SVM) in order to identify pneumonia patterns while providing information about the reliability of the classification. |
JUAN E. ARCO et. al. | arxiv-eess.IV | 2021-03-04 |
| 108 | Inference for Natural Mediation Effects Under Case-cohort Sampling with Applications in Identifying COVID-19 Vaccine Correlates of Protection Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose two approaches to estimation of mediation parameters in the context of case-cohort sampling designs. |
David Benkeser; Iván Díaz; Jialu Ran; | arxiv-stat.ME | 2021-03-03 |
| 109 | COVID-19 and Estimation of Macroeconomic Factors Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This note uses covid indicators to adjust the post-covid data prior to factor estimation. |
Serena Ng; | arxiv-econ.EM | 2021-03-03 |
| 110 | Exploring The Roles of Local Mobility Patterns, Socioeconomic Conditions, and Lockdown Policies in Shaping The Patterns of COVID-19 Spread Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The contributions of this work can be used regardless of the region. |
Mauricio Herrera; | arxiv-stat.AP | 2021-03-03 |
| 111 | The Effects of The NBA COVID Bubble on The NBA Playoffs: A Case Study for Home-Court Advantage Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: The 2020 NBA playoffs were played inside of a bubble in Disney World because of the COVID-19 pandemic. This meant that there were no fans in attendance, games played on neutral … |
Michael Price; Jun Yan; | arxiv-stat.AP | 2021-03-03 |
| 112 | Statistical Methods Used to Combine The Effective Reproduction Number, R(t), and Other Related Measures of COVID-19 in The UK Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: These models differ in their approaches (e.g. mechanistic or empirical) and/or assumptions about spatial or age mixing, and some capture uncertainty in scientific understanding of disease dynamics, and/or have different simplifying assumptions. |
T. MAISHMAN et. al. | arxiv-stat.AP | 2021-03-02 |
| 113 | The `how’ Matters: A Simulation-based Assessment of The Potential Contributions of LFD Tests for School Reopening in England Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We compare a set of potential policies to accompany the reopening of schools by means of an agent-based simulation tool. |
Kevin Kunzmann; Camilla Lingjaerde; Sheila Bird; Sylvia Richardson; | arxiv-stat.AP | 2021-03-02 |
| 114 | Delay Differential Equations for The Spatially-resolved Simulation of Epidemics with Specific Application to COVID-19 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In the present work, we introduce a new variation to such models by using delay differential equations (DDEs). |
Nicola Guglielmi; Elisa Iacomini; Alex Viguerie; | arxiv-math.NA | 2021-03-01 |
| 115 | Towards Understanding The COVID-19 Case Fatality Rate Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We consider two important population covariates, age and GDP as a proxy for the quality and abundance of public health. |
Donghui Yan; Aiyou Chen; Buqing Yang; | arxiv-stat.AP | 2021-03-01 |
| 116 | Comparing Acoustic Analyses of Speech Data Collected Remotely Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: Face-to-face speech data collection has been next to impossible globally due to COVID-19 restrictions. To address this problem, simultaneous recordings of three repetitions of the … |
Cong Zhang; Kathleen Jepson; Georg Lohfink; Amalia Arvaniti; | arxiv-eess.AS | 2021-03-01 |
| 117 | Towards Unbiased COVID-19 Lesion Localisation and Segmentation Via Weakly Supervised Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To support unbiased lesion localisation and to minimise the labeling costs, we propose a data-driven framework supervised by only image-level labels. |
YANG YANG et. al. | arxiv-eess.IV | 2021-03-01 |
| 118 | Spatial Sampling Design to Improve The Efficiency of The Estimation of The Critical Parameters of The SARS-CoV-2 Epidemic Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we extend the proposal of Alleva et al. (2020) to include a spatial sampling mechanism (M\uller, 1998; Grafstr\om et al., 2012, Jauslin and Till\`e, 2020) in the process of data collection to achieve the same level of precision with fewer sample units, thereby facilitating the process of data collection in a situation where timeliness and costs are crucial elements. |
Giorgio Alleva; Giuseppe Arbia; Piero Demetrio Falorsi; Vincenzo Nardelli; Alberto Zuliani; | arxiv-stat.ME | 2021-03-01 |
| 119 | Can Machine Learning Catch The COVID-19 Recession? Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Based on evidence gathered from a newly built large macroeconomic data set for the UK, labeled UK-MD and comparable to similar datasets for the US and Canada, it seems the most promising avenue for forecasting during the pandemic is to allow for general forms of nonlinearity by using machine learning (ML) methods. |
Philippe Goulet Coulombe; Massimiliano Marcellino; Dalibor Stevanovic; | arxiv-econ.EM | 2021-03-01 |
| 120 | Examining Socioeconomic Factors to Understand The Hospital Case-fatality Rates of COVID-19 in The City of Sao Paulo, Brazil Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We examined the variability in HCFRs of COVID-19 in relation to spatial inequalities in socioeconomic factors across the city of Sao Paulo, Brazil. |
CAMILA LORENZ et. al. | arxiv-stat.AP | 2021-02-28 |
| 121 | Estimating and Increasing The Structural Robustness of A Network Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We discuss computational techniques for identifying edges, whose removal may significantly reduce the spectral radius. |
Silvia Noschese; Lothar Reichel; | arxiv-math.NA | 2021-02-27 |
| 122 | Analysis, Prediction, and Control of Epidemics: A Survey from Scalar to Dynamic Network Models Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this survey, we review the history and present the state of the art in the modeling, analysis, and control of epidemic dynamics. |
Lorenzo Zino; Ming Cao; | arxiv-math.DS | 2021-02-27 |
| 123 | Reverse-Bayes Methods: A Review of Recent Technical Advances Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Yet despite the threat posed to the scientific enterprise, there is no agreement concerning alternative approaches. |
Leonhard Held; Robert Matthews; Manuela Ott; Samuel Pawel; | arxiv-stat.ME | 2021-02-26 |
| 124 | CXR-Net: An Artificial Intelligence Pipeline for Quick Covid-19 Screening of Chest X-Rays Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Six distinct cross-validation models, each trained on 1887 images and validated against 378 images, were combined into an ensemble model that was used to classify the CXR images of the test set with resulting Accuracy = 0.789, Precision = 0.739, Recall = 0.693, F1 score = 0.715, ROC(AUC) = 0.852. |
HAIKAL ABDULAH et. al. | arxiv-eess.IV | 2021-02-26 |
| 125 | Variational Full Bayes Lasso: Knots Selection in Regression Splines Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In order to carry through our proposal, a full automatic variational Bayesian Lasso, a Jefferey’s prior is proposed for the hyperparameters and a decision theoretical approach is introduced to decide if a knot is selected or not. |
Larissa Alves; Ronaldo Dias; Helio S. Migon; | arxiv-stat.ME | 2021-02-26 |
| 126 | Semi-supervised Learning for COVID-19 Image Classification Via ResNet Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this challenge, this paper proposes a two-path semi-supervised deep learning model, ssResNet, based on Residual Neural Network (ResNet) for COVID-19 image classification, where two paths refer to a supervised path and an unsupervised path, respectively. |
Lucy Nwosu; Xiangfang Li; Lijun Qian; Seungchan Kim; Xishuang Dong; | arxiv-eess.IV | 2021-02-26 |
| 127 | Exploring The Space-time Pattern of Log-transformed Infectious Count of COVID-19: A Clustering-segmented Autoregressive Sigmoid Model Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a nonparametric graph-based clustering method for discovering dissimilarity of the curve time series in space, which is justified with theoretical support to demonstrate how the model works under mild and easily verified conditions. |
Xiaoping Shi; Meiqian Chen; Yucheng Dong; | arxiv-stat.ME | 2021-02-25 |
| 128 | Hospital Management in The COVID-19 Emergency: Abelian Sandpile Paradigm and Beyond Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, we propose a mathematical model — based on a cellular automaton — for the redistribution of patients within a network of hospitals with limited available resources, in order to reduce the risks of a local/global collapse of the healthcare system. |
Roberta Martucci; Corrado Mascia; Chiara Simeoni; Filippo Tassi; | arxiv-math.OC | 2021-02-23 |
| 129 | Positive Results from UK Single Gene Testing for SARS-COV-2 May Be Inconclusive, Negative or Detecting Past Infections Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This survey reports that a large proportion of positive test results may be based on the detection of a single target gene rather than on two or more target genes as required in the manufacturer instructions for use, and by the WHO in their emergency use assessment. |
Martin Neil; | arxiv-stat.AP | 2021-02-23 |
| 130 | Multi-Feature Multi-Scale CNN-Derived COVID-19 Classification from Lung Ultrasound Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we utilize a deep learning model to perform the classification of COVID-19 from LUS data, which could produce objective diagnostic information for clinicians. |
HUI CHE et. al. | arxiv-eess.IV | 2021-02-23 |
| 131 | RCoNet: Deformable Mutual Information Maximization and High-order Uncertainty-aware Learning for Robust COVID-19 Detection Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To alleviate these concerns, we propose a novel deep network named {\em RCoNet$^k_s$} for robust COVID-19 detection which employs {\em Deformable Mutual Information Maximization} (DeIM), {\em Mixed High-order Moment Feature} (MHMF) and {\em Multi-expert Uncertainty-aware Learning} (MUL). |
Shunjie Dong; Qianqian Yang; Yu Fu; Mei Tian; Cheng Zhuo; | arxiv-eess.IV | 2021-02-22 |
| 132 | Gaussian Process Nowcasting: Application to COVID-19 Mortality Reporting Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a flexible approach using a latent Gaussian process that is capable of describing the changing auto-correlation structure present in the reporting time-delay surface. |
IWONA HAWRYLUK et. al. | arxiv-stat.AP | 2021-02-22 |
| 133 | Estimating SARS-CoV-2 Infections from Deaths, Confirmed Cases, Tests, and Random Surveys Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We develop a simple Bayesian framework to estimate viral prevalence by combining the main available data sources. |
Nicholas J. Irons; Adrian E. Raftery; | arxiv-stat.AP | 2021-02-21 |
| 134 | Tchebichef Transform Domain-based Deep Learning Architecture for Image Super-resolution Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a deep learning based image super-resolution architecture in Tchebichef transform domain. |
Ahlad Kumar; Harsh Vardhan Singh; | arxiv-eess.IV | 2021-02-21 |
| 135 | Classification of COVID-19 Via Homology of CT-SCAN Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, We propose a novel approach to detect SARS-CoV-2 using CT-scan images. |
Sohail Iqbal; H. Fareed Ahmed; Talha Qaiser; Muhammad Imran Qureshi; Nasir Rajpoot; | arxiv-eess.IV | 2021-02-21 |
| 136 | Monitoring The Pandemic: A Fractional Filter for The COVID-19 Contact Rate Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper aims to provide reliable estimates for the COVID-19 contact rate of a Susceptible-Infected-Recovered (SIR) model. |
Tobias Hartl; | arxiv-econ.EM | 2021-02-19 |
| 137 | Capacity Planning for Effective Cohorting of Dialysis Patients During The Coronavirus Pandemic: A Case Study Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we address capacity planning decisions of a hemodialysis clinic located within a major hospital in Istanbul, designated to serve both infected and uninfected patients during the pandemic with limited resources (i.e., dialysis machines). |
CEM BOZKIR et. al. | arxiv-math.OC | 2021-02-18 |
| 138 | Detection and Severity Classification of COVID-19 in CT Images Using Deep Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, a cascaded system is proposed to segment the lung, detect, localize, and quantify COVID-19 infections from computed tomography (CT) images Furthermore, the system classifies the severity of COVID-19 as mild, moderate, severe, or critical based on the percentage of infected lungs. |
YAZAN QIBLAWEY et. al. | arxiv-eess.IV | 2021-02-15 |
| 139 | Fusion of Convolution Neural Network, Support Vector Machine and Sobel Filter for Accurate Detection of COVID-19 Patients Using X-ray Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, a fusion of convolutional neural network (CNN), support vector machine (SVM), and Sobel filter is proposed to detect COVID-19 using X-ray images. |
DANIAL SHARIFRAZI et. al. | arxiv-eess.IV | 2021-02-13 |
| 140 | Adaptive Network Modeling of Social Distancing Interventions Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we build on existing network models for heterogeneous, clustered networks with random link activation/deletion dynamics to put forth realistic mechanisms of social distancing using piecewise constant activation/deletion rates. |
Carl Corcoran; John Michael Clark; | arxiv-math.DS | 2021-02-13 |
| 141 | Control of COVID-19 Dynamics Through A Fractional-order Model Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We investigate, through a fractional mathematical model, the effects of physical distance on the SARS-CoV-2 virus transmission. |
Samia Bushnaq; Tareq Saeed; Delfim F. M. Torres; Anwar Zeb; | arxiv-math.OC | 2021-02-12 |
| 142 | Model-based Prediction and Optimal Control of Pandemics By Nonpharmaceutical Interventions Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Herein, we present the models and algorithms developed by the Alphanumerics Team during the Pandemic Response Challenge. |
Reza Sameni; | arxiv-math.OC | 2021-02-12 |
| 143 | Uncertainty-Aware Semi-supervised Method Using Large Unlabelled and Limited Labeled COVID-19 Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, relying on Generative Adversarial Networks (GAN), we propose a Semi-supervised Classification using Limited Labelled Data (SCLLD) for automated COVID-19 detection. |
ROOHALLAH ALIZADEHSANI et. al. | arxiv-eess.IV | 2021-02-12 |
| 144 | COVID-19 Detection from Scarce Chest X-ray Image Data Using Few-shot Deep Learning Approach Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we have experimented with well-known solutions for data scarcity in deep learning to detect COVID-19. |
Shruti Jadon; | arxiv-eess.IV | 2021-02-11 |
| 145 | Comparative Analysis of Machine Learning Approaches to Analyze and Predict The Covid-19 Outbreak Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a comparative analysis of various ML approaches including Support Vector Machine, Random Forest, K-Nearest Neighbor and Artificial Neural Network in predicting the COVID-19 outbreak in the epidemiological domain. |
MUHAMMAD NAEEM et. al. | arxiv-stat.ML | 2021-02-11 |
| 146 | COVID-19 Identification from Volumetric Chest CT Scans Using A Progressively Resized 3D-CNN Incorporating Segmentation, Augmentation, and Class-rebalancing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This article proposes a 3D Convolutional Neural Network (CNN)-based classification approach considering both the inter- and intra-slice spatial voxel information. |
MD. KAMRUL HASAN et. al. | arxiv-eess.IV | 2021-02-11 |
| 147 | FRM Financial Risk Meter for Emerging Markets Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, a daily systemic risk measure, called FRM (Financial Risk Meter) is proposed. |
Souhir Ben Amor; Michael Althof; Wolfgang Karl Härdle; | arxiv-q-fin.PM | 2021-02-10 |
| 148 | D2A U-Net: Automatic Segmentation of COVID-19 Lesions from CT Slices with Dilated Convolution and Dual Attention Mechanism Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we propose a dilated dual attention U-Net (D2A U-Net) for COVID-19 lesion segmentation in CT slices based on dilated convolution and a novel dual attention mechanism to address the issues above. |
XIANGYU ZHAO et. al. | arxiv-eess.IV | 2021-02-09 |
| 149 | A Bayesian Spatio-temporal Nowcasting Model for Public Health Decision-making and Surveillance Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we develop a Bayesian spatio-temporal nowcasting model for assessing trends in county-level COVID-19 cases in Ohio. |
DAVID KLINE et. al. | arxiv-stat.AP | 2021-02-08 |
| 150 | Analysis of The Effectiveness of Face-Coverings on The Death Rate of COVID-19 Using Machine Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In the current work, we defined a parameter called the average death ratio as the monthly average of the ratio of the number of daily deaths to the total number of daily cases. |
Ali Lafzi; Miad Boodaghi; Siavash Zamani; Niyousha Mohammadshafie; | arxiv-stat.ML | 2021-02-08 |
| 151 | A Novel Multiple Instance Learning Framework for COVID-19 Severity Assessment Via Data Augmentation and Self-supervised Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address these challenges, we propose a novel three-component method, i.e., 1) a deep multiple instance learning component with instance-level attention to jointly classify the bag and also weigh the instances, 2) a bag-level data augmentation component to generate virtual bags by reorganizing high confidential instances, and 3) a self-supervised pretext component to aid the learning process. |
ZEKUN LI et. al. | arxiv-eess.IV | 2021-02-07 |
| 152 | An Interaction Neyman-Scott Point Process Model for Coronavirus Disease-19 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We fit our model to several simulated and real data examples under different outbreak scenarios and show that our method can describe spatial patterns of patient visits well. |
J. Park; W. Chang; B. Choi; | arxiv-stat.AP | 2021-02-05 |
| 153 | Covid-19 Risk Factors: Statistical Learning from German Healthcare Claims Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: As our main methodological contribution, we avoid prior grouping and pre-selection of candidate risk factors. |
Roland Jucknewitz; Oliver Weidinger; Anja Schramm; | arxiv-stat.AP | 2021-02-04 |
| 154 | Tilted Nonparametric Regression Function Estimation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper provides the theory about the convergence rate of the tilted version of linear smoother. |
Farzaneh Boroumand; Mohammad T. Shakeri; Nino Kordzakhia; Mahdi Salehi; Hassan Doosti; | arxiv-stat.ME | 2021-02-03 |
| 155 | A Compartment Model of Human Mobility and Early Covid-19 Dynamics in NYC Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we build a mechanistic system to understand the relation between a reduction in human mobility and Covid-19 spread dynamics within New York City. |
Ian Frankenburg; Sudipto Banerjee; | arxiv-stat.AP | 2021-02-02 |
| 156 | New Estimation Approaches for Graphical Models with Elastic Net Penalty Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In the context of undirected Gaussian graphical models, we introduce three estimators based on elastic net penalty for the underlying dependence graph. |
Davide Bernardini; Sandra Paterlini; Emanuele Taufer; | arxiv-stat.ME | 2021-02-01 |
| 157 | Few-shot Learning for CT Scan Based COVID-19 Diagnosis Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In order to tackle the above issues, we propose a supervised domain adaption based COVID-19 CT diagnostic method which can perform effectively when only a small samples of labeled CT scans are available. |
Yifan Jiang; Han Chen; David K. Han; Hanseok Ko; | arxiv-eess.IV | 2021-01-31 |
| 158 | Monitoring SEIRD Model Parameters Using MEWMA for The COVID-19 Pandemic with Application to The State of Qatar Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work presents a technique for monitoring the pandemic by employing an Susceptible, Exposed, Infected, Recovered Death model regularly estimated by an augmented particle Markov chain Monte Carlo scheme in which the posterior distribution samples are monitored via Multivariate Exponentially Weighted Average process monitoring. |
EDWARD L. BOONE et. al. | arxiv-stat.ME | 2021-01-29 |
| 159 | The Sooner The Better: Lives Saved By The Lockdown During The COVID-19 Outbreak. The Case of Italy Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We use a new estimator, the Augmented Synthetic Control Method (ASCM), that overcomes some limits of the standard Synthetic Control Method (SCM). |
Roy Cerqueti; Raffaella Coppier; Alessandro Girardi; Marco Ventura; | arxiv-econ.EM | 2021-01-28 |
| 160 | Reliable COVID-19 Detection Using Chest X-ray Images Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this need, in this study, we propose a reliable COVID-19 detection network: ReCovNet, which can discriminate COVID-19 pneumonia from 14 different thoracic diseases and healthy subjects. |
Aysen Degerli; Mete Ahishali; Serkan Kiranyaz; Muhammad E. H. Chowdhury; Moncef Gabbouj; | arxiv-eess.IV | 2021-01-28 |
| 161 | Seroprevalence of SARS-CoV-2 Antibodies in South Korea Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We analyze the seroprevalence surveys using a Bayesian method with an informative prior distribution on the seroprevalence parameter, and the sensitivity and specificity of the diagnostic test. |
Kwangmin Lee; Seongil Jo; Jaeyong Lee; | arxiv-stat.AP | 2021-01-28 |
| 162 | An Explainable AI System for Automated COVID-19 Assessment and Lesion Categorization from CT-scans Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we propose an AI-powered pipeline, based on the deep-learning paradigm, for automated COVID-19 detection and lesion categorization from CT scans. |
MATTEO PENNISI et. al. | arxiv-eess.IV | 2021-01-28 |
| 163 | The Probabilistic Final Standing Calculator: A Fair Stochastic Tool to Handle Abruptly Stopped Football Seasons IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce a tool to calculate in a fairer way the final standings of domestic leagues that have to stop prematurely: our Probabilistic Final Standing Calculator (PFSC). |
Hans Van Eetvelde; Lars Magnus Hvattum; Christophe Ley; | arxiv-stat.AP | 2021-01-26 |
| 164 | Efficient Multi-objective Evolutionary 3D Neural Architecture Search for COVID-19 Detection with Chest CT Scans IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes an efficient Evolutionary Multi-objective neural ARchitecture Search (EMARS) framework, which can automatically search for 3D neural architectures based on a well-designed search space for COVID-19 chest CT scan classification. |
Xin He; Shihao Wang; Guohao Ying; Jiyong Zhang; Xiaowen Chu; | arxiv-eess.IV | 2021-01-26 |
| 165 | Kinetic Derivation of A Time-dependent SEIRD Reaction-diffusion System for COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a time-dependent Susceptible-Exposed-Infectious-Recovered-Died (SEIRD) reaction-diffusion system for the COVID-19 pandemic and we deal with its derivation from a kinetic model. |
Mohamed Zagour; | arxiv-math.AP | 2021-01-26 |
| 166 | A Nowcasting Approach to Generate Timely Estimates of Mexican Economic Activity: An Application to The Period of COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a new approach based on dynamic factor models (DFMs) to perform nowcasts for the percentage annual variation of the Mexican Global Economic Activity Indicator (IGAE in Spanish). |
Francisco Corona; Graciela González-Farías; Jesús López-Pérez; | arxiv-stat.AP | 2021-01-25 |
| 167 | Low Incidence Rate of COVID-19 Undermines Confidence in Estimation of The Vaccine Efficacy IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, we show using a probabilistic model that uncertainty in the efficacy rate could be underestimated when the disease risk is low. |
Yasin Memari; | arxiv-stat.ME | 2021-01-25 |
| 168 | A Two-step Explainable Approach for COVID-19 Computer-aided Diagnosis from Chest X-ray Images IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our approach achieves promising performance in COVID detection, compatible with expert human radiologists. |
Carlo Alberto Barbano; Enzo Tartaglione; Claudio Berzovini; Marco Calandri; Marco Grangetto; | arxiv-eess.IV | 2021-01-25 |
| 169 | 3D U-Net for Segmentation of COVID-19 Associated Pulmonary Infiltrates Using Transfer Learning: State-of-the-art Results on Affordable Hardware IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we therefore developed and tested a solution on how transfer learning can be used to train state-of-the-art segmentation models on limited hardware and in shorter time. |
KENO K. BRESSEM et. al. | arxiv-eess.IV | 2021-01-25 |
| 170 | An Environmentally-Adaptive Hawkes Process with An Application to COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We proposed a new generalized model based on the classical Hawkes process with environmental multipliers, which is called an environmentally-adaptive Hawkes (EAH) model. |
Tingnan Gong; Yu Chen; Weiping Zhang; | arxiv-stat.AP | 2021-01-25 |
| 171 | Projected Statistical Methods for Distributional Data on The Real Line with The Wasserstein Metric IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a novel class of projected methods, to perform statistical analysis on a data set of probability distributions on the real line, with the 2-Wasserstein metric. |
Matteo Pegoraro; Mario Beraha; | arxiv-stat.ME | 2021-01-22 |
| 172 | Developments and Applications of Shapley Effects to Reliability-oriented Sensitivity Analysis with Correlated Inputs IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes new target sensitivity indices, based on the Shapley values and called target Shapley effects, allowing for interpretable influence measures of each input in the case of dependence between the inputs. |
Marouane Il Idrissi; Vincent Chabridon; Bertrand Iooss; | arxiv-math.ST | 2021-01-20 |
| 173 | Chest X-ray Lung and Heart Segmentation Based on Minimal Training Sets IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In our paper, we present a deep neural network to which we refer to as Attention BCDU-Net, and apply it to the task of lung and heart segmentation from chest X-ray (CXR) images, a basic but ardous step in the diagnostic pipeline, for instance for the detection of cardiomegaly. |
Balázs Maga; | arxiv-eess.IV | 2021-01-20 |
| 174 | Estimation of The Distribution of The Individual Reproduction Number: The Case of The COVID-19 Pandemic IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We investigate the problem of estimating the distribution of the individual reproduction number governing the COVID-19 pandemic. |
Alexander Braumann; Jonas Krampe; Jens-Peter Kreiss; Efstathios Paparoditis; | arxiv-stat.AP | 2021-01-19 |
| 175 | Classification of COVID-19 X-ray Images Using A Combination of Deep and Handcrafted Features IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we demonstrate the efficacy of a support vector machine (SVM) classifier, trained with a combination of deep convolutional and handcrafted features extracted from X-ray chest scans. |
Weihan Zhang; Bryan Pogorelsky; Mark Loveland; Trevor Wolf; | arxiv-eess.IV | 2021-01-19 |
| 176 | COVID-Net CT-2: Enhanced Deep Neural Networks for Detection of COVID-19 from Chest CT Images Through Bigger, More Diverse Learning IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we introduce COVID-Net CT-2, enhanced deep neural networks for COVID-19 detection from chest CT images trained on the largest quantity and diversity of multinational patient cases in research literature. We introduce two new CT benchmark datasets, the largest comprising a multinational cohort of 4,501 patients from at least 15 countries. |
Hayden Gunraj; Ali Sabri; David Koff; Alexander Wong; | arxiv-eess.IV | 2021-01-18 |
| 177 | Covid-19 Classification with Deep Neural Network and Belief Functions IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a belief function-based convolutional neural network with semi-supervised training to detect Covid-19 cases. |
Ling Huang; Su Ruan; Thierry Denoeux; | arxiv-eess.IV | 2021-01-18 |
| 178 | Quantifying Uncertainty in Infectious Disease Mechanistic Models IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We describe the statistical uncertainty as belonging to three categories: data uncertainty, stochastic uncertainty, and structural uncertainty. |
Lucy D’Agostino McGowan; Kyra H. Grantz; Eleanor Murray; | arxiv-stat.ME | 2021-01-18 |
| 179 | Optimal Intervention Strategies to Mitigate The COVID-19 Pandemic Effects IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Motivated by this, we consider the problem of forming intervention strategies to mitigate the impact of the COVID-19 pandemic that optimize the trade-off between the number of deceases and the socio-economic costs. |
Andreas Kasis; Stelios Timotheou; Nima Monshizadeh; Marios Polycarpou; | arxiv-math.OC | 2021-01-15 |
| 180 | A Multi-Stage Attentive Transfer Learning Framework for Improving COVID-19 Diagnosis IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a multi-stage attentive transfer learning framework for improving COVID-19 diagnosis. |
Yi Liu; Shuiwang Ji; | arxiv-eess.IV | 2021-01-13 |
| 181 | Automated Model Design and Benchmarking of 3D Deep Learning Models for COVID-19 Detection with Chest CT Scans IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Many recent studies have shown that deep learning (DL) based solutions can help detect COVID-19 based on chest CT scans. |
XIN HE et. al. | arxiv-eess.IV | 2021-01-13 |
| 182 | Estimating Functional Parameters for Understanding The Impact of Weather and Government Interventions on COVID-19 Outbreak IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The model uses Bayesian inference with Gaussian process priors to study the functional parameters nonparametrically, and sensitivity analysis is adopted to investigate the main and interaction effects of these factors. |
Chih-Li Sung; | arxiv-stat.AP | 2021-01-13 |
| 183 | Resiliency of On-Demand Multimodal Transit Systems During A Pandemic IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: It presents a case study for the city of Atlanta and evaluates ODMTS for multiple scenarios of depressed demand and social distancing representing various stages of the pandemic. |
RAMON AUAD et. al. | arxiv-math.OC | 2021-01-13 |
| 184 | Decision Support for COVID-19 Policy Including Poverty Drivers IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we present a multi-attribute decision support framework for choosing between countermeasure strategies designed to mitigate the effects of COVID-19 in the UK. |
PETER STRONG et. al. | arxiv-stat.AP | 2021-01-12 |
| 185 | Quickest Detection and Forecast of Pandemic Outbreaks: Analysis of COVID-19 Waves IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, we propose an integrated detection-estimation-forecasting framework that, using publicly available data, is designed to: (i) learn relevant features of the pandemic (e.g., the infection rate); (ii) detect as quickly as possible the onset (or the termination) of an exponential growth of the contagion; and (iii) reliably forecast the pandemic evolution. |
GIOVANNI SOLDI et. al. | arxiv-eess.SP | 2021-01-12 |
| 186 | The ‘COVID’ Crash of The 2020 U.S. Stock Market IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We employed the log-periodic power law singularity (LPPLS) methodology to systematically investigate the 2020 stock market crash in the U.S. equities sectors with different levels of total market capitalizations through four major U.S. stock market indexes, including the Wilshire 5000 Total Market index, the S&P 500 index, the S&P MidCap 400 index, and the Russell 2000 index, representing the stocks overall, the large capitalization stocks, the middle capitalization stocks and the small capitalization stocks, respectively. |
Min Shu; Ruiqiang Song; Wei Zhu; | arxiv-q-fin.RM | 2021-01-10 |
| 187 | Monitoring The COVID-19 Epidemic with Nationwide Telecommunication Data IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here, we perform a large-scale, spatio-temporal analysis of human mobility during the COVID-19 epidemic. |
Joel Persson; Jurriaan F. Parie; Stefan Feuerriegel; | arxiv-stat.AP | 2021-01-07 |
| 188 | Statistical Challenges in The Analysis of Sequence and Structure Data for The COVID-19 Spike Protein IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present statistical approaches to tackle some challenges associated with the analysis of S-protein data. |
Shiyu He; Samuel W. K. Wong; | arxiv-stat.AP | 2021-01-06 |
| 189 | Tractable Bayes of Skew-Elliptical Link Models for Correlated Binary Data IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here, we propose a multivariate skew-elliptical link model for correlated binary responses, which includes the multivariate probit model as a special case. |
Zhongwei Zhang; Reinaldo B. Arellano-Valle; Marc G. Genton; Raphaël Huser; | arxiv-stat.ME | 2021-01-06 |
| 190 | Assessing Vaccine Durability in Randomized Trials Following Placebo Crossover IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We develop different methods to estimate efficacy within the context of a proportional hazards regression model and explore via simulation the implications of placebo crossover for estimation of vaccine efficacy under different efficacy dynamics and study designs. |
Jonathan Fintzi; Dean Follmann; | arxiv-stat.AP | 2021-01-04 |
| 191 | Dynamics, Behaviours, and Anomaly Persistence in Cryptocurrencies and Equities Surrounding COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper uses new and recently introduced methodologies to study the similarity in the dynamics and behaviours of cryptocurrencies and equities surrounding the COVID-19 pandemic. |
Nick James; | arxiv-q-fin.ST | 2021-01-03 |
| 192 | CovTANet: A Hybrid Tri-level Attention Based Network For Lesion Segmentation, Diagnosis, And Severity Prediction Of COVID-19 Chest CT Scans IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, a hybrid neural network is proposed, named CovTANet, to provide an end-to-end clinical diagnostic tool for early diagnosis, lesion segmentation, and severity prediction of COVID-19 utilizing chest computer tomography (CT) scans. |
TANVIR MAHMUD et. al. | arxiv-eess.IV | 2021-01-03 |
| 193 | Advanced And Comprehensive Research On The Dynamics Of COVID-19 Under Mass Communication Outlets Intervention And Quarantine Strategy: A Deterministic And Probabilistic Approach IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Along the same line, we aim during this study to generalize and ameliorate many existing works that consecrated to analyse the behaviour of this epidemic. |
Driss Kiouach; Salim El Azami El-idrissi; Yassine Sabbar; | arxiv-math.DS | 2021-01-02 |
| 194 | Home Advantage of European Major Football Leagues Under COVID-19 Pandemic IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The main objective of this study is a quantitative evaluation of “crowd effects” on home advantage, using the results of these closed matches. |
Eiji Konaka; | arxiv-stat.AP | 2021-01-02 |
| 195 | A New Framework For Inference On Markov Population Models IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we construct a joint Gaussian likelihood for approximate inference on Markov population models. |
Adam Walder; Ephraim M. Hanks; | arxiv-stat.ME | 2021-01-02 |
| 196 | COVID-19 Spreading In Financial Networks: A Semiparametric Matrix Regression Model IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a new semiparametric model for temporal multilayer causal networks with both intra- and inter-layer connectivity. |
Billio Monica; Casarin Roberto; Costola Michele; Iacopini Matteo; | arxiv-econ.EM | 2021-01-02 |
| 197 | The 2020 Global Stock Market Crash: Endogenous Or Exogenous? IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we applied the log-periodic power law singularity (LPPLS) methodology based on multilevel time series to unravel the underlying mechanisms of the 2020 global stock market crash by analyzing the trajectories of 10 major stock market indexes from both developed and emergent stock markets, including the S&P 500, DJIA, NASDAQ, FTSE, DAX, NIKKEI, CSI 300, HSI, BSESN, and BOVESPA. |
Ruiqiang Song; Min Shu; Wei Zhu; | arxiv-q-fin.RM | 2021-01-01 |
| 198 | How Do Mobility Restrictions And Social Distancing During COVID-19 Affect The Crude Oil Price? IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We use quantile regression and stationary and non-stationary extreme value models to study the impact. |
Asim K. Dey; Kumer P. Das; | arxiv-stat.AP | 2021-01-01 |
| 199 | Dynamical Characterization Of Antiviral Effects In COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, based on the concept of virus spreadability in the host, antiviral effectiveness thresholds are determined to establish whether or not a treatment will be able to clear the infection. |
Pablo Abuin; Alejandro Anderson; Antonio Ferramosca; Esteban A. Hernandez-Vargas; Alejandro H. Gonzalez; | arxiv-math.DS | 2020-12-31 |
| 200 | Exploiting Shared Knowledge From Non-COVID Lesions For Annotation-Efficient COVID-19 CT Lung Infection Segmentation IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel relation-driven collaborative learning model for annotation-efficient COVID-19 CT lung infection segmentation. |
YICHI ZHANG et. al. | arxiv-eess.IV | 2020-12-31 |
| 201 | Bayesian State Space Modelling For COVID-19: With Tennessee And New York Case Studies IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We develop a Bayesian inferential framework for the spread of COVID-19 using mechanistic epidemiological models, such as SIR or SEIR, and allow the effective contact rate to vary in time. |
Adam Spannaus; Theodore Papamarkou; Samantha Erwin; J. Blair Christian; | arxiv-stat.ME | 2020-12-30 |
| 202 | An Analysis To Identify The Structural Breaks Of COVID-19 In Turkey IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: For this purpose, in this study, the breakpoint linear regression analysis is performed to analyze the trends of daily active cases, recovered, and deaths in Turkey. |
Yeşim Güney; Yetkin Tuaç; Şenay Özdemir; Fulya Gökalp Yavuz; Olcay Arslan; | arxiv-stat.AP | 2020-12-30 |
| 203 | New Bag of Deep Visual Words Based Features to Classify Chest X-ray Images for COVID-19 Diagnosis IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a new BoVW method over deep features, called Bag of Deep Visual Words (BoDVW), by removing the feature map normalization step and adding deep features normalization step on the raw feature maps. |
Chiranjibi Sitaula; Sunil Aryal; | arxiv-eess.IV | 2020-12-30 |
| 204 | Survey Of The Detection And Classification Of Pulmonary Lesions Via CT And X-Ray IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This article reviews pulmonary CT and X-ray image detection and classification in the last decade. Furthermore, this review introduces 26 commonly used public medical image datasets, summarizes the latest technology, and discusses current challenges and future research directions. |
Yixuan Sun; Chengyao Li; Qian Zhang; Aimin Zhou; Guixu Zhang; | arxiv-eess.IV | 2020-12-30 |
| 205 | Estimating The Change In Soccer’s Home Advantage During The Covid-19 Pandemic Using Bivariate Poisson Regression IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To date, most of this post-Covid soccer research has used linear regression models, or versions thereof, to estimate potential changes to the home advantage. |
Luke S. Benz; Michael J. Lopez; | arxiv-stat.AP | 2020-12-29 |
| 206 | Development and Evaluation of A 3D Annotation Software for Interactive COVID-19 Lesion Segmentation in Chest CT IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a new interactive and user-friendly tool for COVID-19 lesion segmentation, which works by alternating automatic steps (based on level-set segmentation and statistical shape modeling) with manual correction steps. |
SIMONE BENDAZZOLI et. al. | arxiv-eess.IV | 2020-12-29 |
| 207 | Diagnosis/Prognosis Of COVID-19 Images: Challenges, Opportunities, And Applications IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, we aim to present an overview of the current state, challenges, and opportunities of developing SP/DL-empowered models for diagnosis (screening/monitoring) and prognosis (outcome prediction and severity assessment) of COVID-19 infection. |
ARASH MOHAMMADI et. al. | arxiv-eess.IV | 2020-12-28 |
| 208 | Screening COVID-19 Based On CT/CXR Images & Building A Publicly Available CT-scan Dataset Of COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To date, researchers have proposed several different screening methods; however, none of them could achieve a reliable and highly sensitive performance yet. To tackle such limitations, this study firstly builds a large-size publicly available CT-scan dataset, consisting of more than 13k CT-images of more than 1000 individuals, in which 8k images are taken from 500 patients infected with COVID-19. |
Maryam Dialameh; Ali Hamzeh; Hossein Rahmani; Amir Reza Radmard; Safoura Dialameh; | arxiv-eess.IV | 2020-12-28 |
| 209 | Estimating Impacts Of Covid19 On Transport Capacity In Railway Networks IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, the transport capacity of a PT network is assessed, using a mathematical passenger route choice and train scheduling model. |
Nikola Bešinović; Christopher Szymula; | arxiv-math.OC | 2020-12-26 |
| 210 | COVIDX: Computer-aided Diagnosis Of Covid-19 And Its Severity Prediction With Raw Digital Chest X-ray Images IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we present an automatic COVID-19 diagnostic and severity prediction (COVIDX) system that uses deep feature maps from CXR images to diagnose COVID-19 and its severity prediction. |
Wajid Arshad Abbasi; Syed Ali Abbas; Saiqa Andleeb; | arxiv-eess.IV | 2020-12-25 |
| 211 | Objective Evaluation Of Deep Uncertainty Predictions For COVID-19 Detection IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here we apply and evaluate three uncertainty quantification techniques for COVID-19 detection using chest X-Ray (CXR) images. |
HAMZEH ASGHARNEZHAD et. al. | arxiv-eess.IV | 2020-12-22 |
| 212 | Efficient And Visualizable Convolutional Neural Networks For COVID-19 Classification Using Chest CT IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we evaluated and compared 40 different convolutional neural network architectures for COVID-19 diagnosis, serving as the first to consider the EfficientNet family for COVID-19 diagnosis. |
Aksh Garg; Sana Salehi; Marianna La Rocca; Rachael Garner; Dominique Duncan; | arxiv-eess.IV | 2020-12-22 |
| 213 | COVID-19: Optimal Design Of Serosurveys For Disease Burden Estimation IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We provide a methodology by which an epidemiologist may arrive at an optimal design for a survey whose goal is to estimate the disease burden in a population. |
SIVA ATHREYA et. al. | arxiv-stat.AP | 2020-12-22 |
| 214 | COVID-19 And Other Viruses: Holding Back Its Expansion By Massive Testing IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a modified SEIR model which takes into account tracing and massive testing, proving theoretically that more tracing and testing implies a reduction of the total number of infected people in the long run. |
José Luis Sainz-Pardo; José Valero; | arxiv-stat.AP | 2020-12-22 |
| 215 | Binary Classification Tests, Imperfect Standards, and Ambiguous Information IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, I argue that the new test can be described as producing ambiguous information when the pre-established is imperfect. As an example, I present hypothetical test data satisfying the WHO’s minimum quality requirement for rapid Antigen tests which leads to dilation. Using results from Copula theory, I construct the (usually non-singleton) set of all these possible joint distributions, which allows me to assess the new test’s informativeness. |
Gabriel Ziegler; | arxiv-econ.EM | 2020-12-21 |
| 216 | Global Trends and Predictors of Face Mask Usage During The COVID-19 Pandemic IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Methods: We examined a total of 13,723,810 responses to a daily cross-sectional representative online survey in 38 countries who completed from April 23, 2020 to October 31, 2020 and reported having been in public at least once during the last seven days. |
ELENA BADILLO-GOICOECHEA et. al. | arxiv-stat.AP | 2020-12-21 |
| 217 | The Impact Of Temperature And Isolation On COVID-19 In India: A Mathematical Modelling Approach Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: The dynamics of COVID-19 in India are captured using a set of delay differential equations by dividing a constant population into six compartments. The equilibrium points are … |
D Bhanu Prakash; Bishal Chhetri; D K K Vamsi; Balasubramanian S; Carani B Sanjeevi; | arxiv-math.DS | 2020-12-21 |
| 218 | Deep Learning In Detection And Diagnosis Of Covid-19 Using Radiology Modalities: A Systematic Review Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Accordingly, medical and computer researchers tended to use machine-learning models to analyze radiology images. |
Mustafa Ghaderzadeh; Farkhondeh Asadi; | arxiv-eess.IV | 2020-12-21 |
| 219 | Prevalence Estimation From Random Samples And Census Data With Participation Bias IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We derive (maximum likelihood and method of moment) prevalence estimators, based on a survey sample, that additionally utilize the official information, and that are substantially more accurate than the simple sample proportion of positive cases. |
Stéphane Guerrier; Christoph Kuzmics; Maria-Pia Victoria-Feser; | arxiv-stat.ME | 2020-12-19 |
| 220 | Constructing and Evaluating An Explainable Model for COVID-19 Diagnosis from Chest X-rays IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, our focus is on constructing models to assist a clinician in the diagnosis of COVID-19 patients in situations where it is easier and cheaper to obtain X-ray data than to obtain high-quality images like those from CT scans. |
Rishab Khincha; Soundarya Krishnan; Tirtharaj Dash; Lovekesh Vig; Ashwin Srinivasan; | arxiv-eess.IV | 2020-12-19 |
| 221 | Revisiting ICH E9 (R1) During The COVID-19 Pandemic Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article we revisit recent research on estimands and handling of missing values, especially the ICH E9 (R1) on Estimands and Sensitivity Analysis in Clinical Trials. |
Yongming Qu; Ilya Lipkovich; | arxiv-stat.ME | 2020-12-19 |
| 222 | Translation-invariant Functional Clustering On COVID-19 Deaths Adjusted On Population Risk Factors Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a novel three-step clustering method to circumvent these issues. |
Amay SM Cheam; Marc Fredette; Matthieu Marbac; Fabien Navarro; | arxiv-stat.AP | 2020-12-19 |
| 223 | Modeling And Simulating The Spatial Spread Of An Epidemic Through Multiscale Kinetic Transport Equations IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we propose a novel space-dependent multiscale model for the spread of infectious diseases in a two-dimensional spatial context on realistic geographical scenarios. |
Walter Boscheri; Giacomo Dimarco; Lorenzo Pareschi; | arxiv-math.NA | 2020-12-18 |
| 224 | Classification Under Uncertainty: Data Analysis for Diagnostic Antibody Testing IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a novel method that leverages optimal decision theory to address this problem. |
Paul N. Patrone; Anthony J. Kearsley; | arxiv-stat.ME | 2020-12-17 |
| 225 | Group Testing And PCR: A Tale Of Charge Value IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We study here the use that can be made of this extra piece of information to construct a one-stage pool testing algorithms on an idealize version of this model. |
Emilien Joly; Bastien Mallein; | arxiv-stat.AP | 2020-12-16 |
| 226 | COVID-19 Effect On Consumer Spending And Foot Traffic IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Using anonymized card transactions and mobile device-based location tracking data, we analyze the factors that contribute to these behavior changes, focusing on stimulus check issuance and state-wide reopening. |
Zhiqing Yang; Youngjun Choe; Matthew Martell; | arxiv-stat.AP | 2020-12-14 |
| 227 | Hospital Capacity Planning Using Discrete Event Simulation Under Special Consideration Of The COVID-19 Pandemic IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a resource-planning tool for hospitals under special consideration of the COVID-19 pandemic, called babsim.hospital. |
Thomas Bartz-Beielstein; Frederik Rehbach; Olaf Mersmann; Eva Bartz; | arxiv-stat.AP | 2020-12-13 |
| 228 | CHS-Net: A Deep Learning Approach for Hierarchical Segmentation of COVID-19 Infected CT Images IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In the present article, an automated deep learning based model, COVID-19 hierarchical segmentation network (CHS-Net) is proposed that functions as a semantic hierarchical segmenter to identify the COVID-19 infected regions from lungs contour via CT medical imaging. |
Narinder Singh Punn; Sonali Agarwal; | arxiv-eess.IV | 2020-12-13 |
| 229 | Optimal Policies for A Pandemic: A Stochastic Game Approach and A Deep Learning Algorithm IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a multi-region SEIR model based on stochastic differential game theory, aiming to formulate optimal regional policies for infectious diseases. |
Yao Xuan; Robert Balkin; Jiequn Han; Ruimeng Hu; Hector D. Ceniceros; | arxiv-math.OC | 2020-12-12 |
| 230 | Semiparametric Causal Mediation Analysis Under Unmeasured Mediator-outcome Confounding IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose semiparametric identification of natural direct and indirect effects in the presence of unmeasured mediator-outcome confounding by leveraging heteroskedasticity restrictions on the observed data law. |
BaoLuo Sun; | arxiv-stat.ME | 2020-12-12 |
| 231 | AIforCOVID: Predicting The Clinical Outcomes In Patients With COVID-19 Applying AI To Chest-X-rays. An Italian Multicentre Study IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we investigate whether chest X-ray (CXR) can be used as a possible tool for the early identification of patients at risk of severe outcome, like intensive care or death. We present a dataset including data collected from 820 patients by six Italian hospitals in spring 2020 during the first COVID-19 emergency. |
PAOLO SODA et. al. | arxiv-eess.IV | 2020-12-11 |
| 232 | Optimal Control Studies On Age Structural Modeling Of COVID-19 In Presence Of Saturated Medical Treatment Of Holling Type III IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study initially, we propose an age structured model and calculate the equilibrium points and basic reproduction number. Later we propose an optimal control problem to understand the roles of treatment in controlling the epidemic. |
Bishal Chhetri; D. K. K Vamsi; Carani B Sanjeevi; | arxiv-math.DS | 2020-12-11 |
| 233 | Context Matters: Graph-based Self-supervised Representation Learning For Medical Images IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a novel approach with two levels of self-supervised representation learning objectives: one on the regional anatomical level and another on the patient-level. |
Li Sun; Ke Yu; Kayhan Batmanghelich; | arxiv-eess.IV | 2020-12-11 |
| 234 | Checklist for Responsible Deep Learning Modeling of Medical Images Based on COVID-19 Detection Studies Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we carry out a systematic analysis of various aspects of proposed models. |
WERONIKA HRYNIEWSKA et. al. | arxiv-eess.IV | 2020-12-11 |
| 235 | Mathematical Model Optimized For Prediction And Health Care Planning For COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The objective was to develop a mathematical model designed to optimize predictions related to the need for hospitalization and ICU admission by COVID-19 patients. |
JOSE MANUEL GARRIDO et. al. | arxiv-math.DS | 2020-12-10 |
| 236 | COVID-MTL: Multitask Learning With Shift3D And Random-weighted Loss For Automated Diagnosis And Severity Assessment Of COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present an end-to-end multitask learning (MTL) framework (COVID-MTL) that is capable of automated and simultaneous detection (against both radiology and NAT) and severity assessment of COVID-19. |
GUOQING BAO et. al. | arxiv-eess.IV | 2020-12-10 |
| 237 | Effect Of Different Batch Size Parameters On Predicting Of COVID19 Cases IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, the effect of different batch size (BH=3, 10, 20, 30, 40, and 50) parameter values on their performance in detecting COVID19 and other classes was investigated using data belonging to 4 different (Viral Pneumonia, COVID19, Normal, Bacterial Pneumonia) classes. |
Ali Narin; Ziynet Pamuk; | arxiv-eess.IV | 2020-12-10 |
| 238 | Detection Of Covid-19 Patients With Convolutional Neural Network Based Features On Multi-class X-ray Chest Images IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, chest X-ray images, which can be accessed easily and quickly, were used because the covid-19 attacked the respiratory systems. |
Ali Narin; | arxiv-eess.IV | 2020-12-10 |
| 239 | Ensemble-CVDNet: A Deep Learning Based End-to-End Classification Framework For COVID-19 Detection Using Ensembles Of Networks IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, we have focused on X-Ray images and developed an end-to-end deep learning model, i.e. Ensemble-CVDNet, to distinguish COVID-19 pneumonia from non-COVID pneumonia and healthy cases in this work. |
Coşku Öksüz; Oğuzhan Urhan; Mehmet Kemal Güllü; | arxiv-eess.IV | 2020-12-09 |
| 240 | Unpacking The Drop In COVID-19 Case Fatality Rates: A Study Of National And Florida Line-Level Data IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: By accounting for several confounding factors, our analysis shows how age-stratified HFR can provide a more realistic picture of treatment improvements than CFR. |
Cheng Cheng; Helen Zhou; Jeremy C. Weiss; Zachary C. Lipton; | arxiv-stat.AP | 2020-12-08 |
| 241 | COVID-19 Detection In Chest X-Ray Images Using A New Channel Boosted CNN IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, a new classification technique CB-STM-RENet based on deep Convolutional Neural Network (CNN) and Channel Boosting is proposed for the screening of COVID-19 in chest X-Rays. |
Saddam Hussain Khan; Anabia Sohail; Asifullah Khan; | arxiv-eess.IV | 2020-12-08 |
| 242 | Social Media Unrest Prediction During The {COVID}-19 Pandemic: Neural Implicit Motive Pattern Recognition As Psychometric Signs Of Severe Crises IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present psychologically validated social unrest predictors and replicate scalable and automated predictions, setting a new state of the art on a recent German shared task dataset. |
Dirk Johannßen; Chris Biemann; | arxiv-stat.ML | 2020-12-08 |
| 243 | Adaptive Sampling For Estimating Distributions: A Bayesian Upper Confidence Bound Approach IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: A Bayesian variant of the existing upper confidence bound (UCB) based approaches is proposed. |
Dhruva Kartik; Neeraj Sood; Urbashi Mitra; Tara Javidi; | arxiv-stat.ME | 2020-12-07 |
| 244 | The Role Of Regularization In Shaping Weight And Node Pruning Dependency And Dynamics IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a novel framework for weight pruning by sampling from a probability function that favors the zeroing of smaller weights. |
Yael Ben-Guigui; Jacob Goldberger; Tammy Riklin-Raviv; | arxiv-eess.IV | 2020-12-07 |
| 245 | Pandemic Risk Management: Resources Contingency Planning And Allocation IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The paper investigates contingency planning and resources allocation from a risk management perspective, as opposed to the prevailing supply chain perspective. |
Xiaowei Chen; Wing Fung Chong; Runhuan Feng; Linfeng Zhang; | arxiv-q-fin.RM | 2020-12-06 |
| 246 | Statistical Properties Of The Aftershocks Of Stock Market Crashes: Evidence Based On The 1987 Crash, 2008 Financial Crisis And COVID-19 Pandemic IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The analysis shows that high magnitude aftershocks comparable to the mainshock are rare but low magnitude aftershocks can be seen frequently till the full recovery of the market. |
Anish Rai; Ajit Mahata; Md Nurujjaman; Om Prakash; | arxiv-q-fin.ST | 2020-12-05 |
| 247 | Network Group Testing IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we utilize network information to improve group testing. |
Paolo Bertolotti; Ali Jadbabaie; | arxiv-stat.AP | 2020-12-04 |
| 248 | Inference In Mixed Causal And Noncausal Models With Generalized Student’s T-distributions IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: For this purpose, we propose a new approach to make inference on causal and noncausal parameters in finite sample sizes. |
Francesco Giancaterini; Alain Hecq; | arxiv-econ.EM | 2020-12-03 |
| 249 | Reallocating And Sharing Health Equipments In Sanitary Emergency Situations: The COVID-19 Case In Spain IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we provide a mathematical programming based decision tool to optimally reallocate and share equipments between different units in emergency situations under lack of resources. |
Víctor Blanco; Ricardo Gázquez; Marina Leal; | arxiv-math.OC | 2020-12-03 |
| 250 | COVID-CLNet: COVID-19 Detection With Compressive Deep Learning Approaches IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, to assist the radiologist or other medical professional to detect and identify the COVID-19 cases in the shortest possible time, we propose a computer-aided detection (CADe) system that uses the computed tomography (CT) scan images. |
Khalfalla Awedat; Almabrok Essa; | arxiv-eess.IV | 2020-12-03 |
| 251 | Filtering And Improved Uncertainty Quantification In The Dynamic Estimation Of Effective Reproduction Numbers IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We use a conjugate analysis, and all calculations are explicit. |
Marcos A. Capistrán; Antonio Capella; J. Andrés Christen; | arxiv-stat.ME | 2020-12-03 |
| 252 | Efficient Social Distancing For COVID-19: An Integration Of Economic Health And Public Health IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose to solve the problem with a deep-learning approach. |
Kexin Chen; Chi Seng Pun; Hoi Ying Wong; | arxiv-stat.AP | 2020-12-03 |
| 253 | Assaying Large-scale Testing Models to Interpret COVID-19 Case Numbers Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We develop mathematical models based on competing hypotheses regarding this link, thereby providing different prevalence estimates based on case numbers, and validate them by predicting SARS-CoV-2-attributed death rate trajectories. |
Michel Besserve; Simon Buchholz; Bernhard Schölkopf; | arxiv-stat.AP | 2020-12-03 |
| 254 | Fighting Together Against The Pandemic: Learning Multiple Models On Tomography Images For COVID-19 Diagnosis IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we adopt pretrained deep convolutional neural network architectures in order to diagnose COVID-19 disease on CT images. |
Mario Manzo; Simone Pellino; | arxiv-eess.IV | 2020-12-02 |
| 255 | Bull And Bear Markets During The COVID-19 Pandemic IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Using the model of Maheu, McCurdy and Song (2012), we provide smoothed estimates and out-of-sample forecasts associated with stock market dynamics during the pandemic. |
John M. Maheu; Thomas H. McCurdy; Yong Song; | arxiv-econ.EM | 2020-12-02 |
| 256 | CovSegNet: A Multi Encoder-Decoder Architecture For Improved Lesion Segmentation Of COVID-19 Chest CT Scans IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, an automated COVID-19 lesion segmentation scheme is proposed utilizing a highly efficient neural network architecture, namely CovSegNet, to overcome these limitations. |
Tanvir Mahmud; Md Awsafur Rahman; Shaikh Anowarul Fattah; Sun-Yuan Kung; | arxiv-eess.IV | 2020-12-02 |
| 257 | Data-driven Optimal Control Of A SEIR Model For COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a data-driven optimal control approach which integrates the reported partial data with the epidemic dynamics for COVID-19. |
Hailiang Liu; Xuping Tian; | arxiv-math.OC | 2020-12-01 |
| 258 | Semi-Mechanistic Bayesian Modeling Of COVID-19 With Renewal Processes IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a general Bayesian approach to modeling epidemics such as COVID-19. |
SAMIR BHATT et. al. | arxiv-stat.AP | 2020-12-01 |
| 259 | Forecasting Confirmed Cases Of The COVID-19 Pandemic With A Migration-based Epidemiological Model IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This drives us to formulate a new infectious dynamic model for forecasting the COVID-19 pandemic within the human mobility network, named the SaucIR-model in the sense that the new compartmental model extends the benchmark SIR model by dividing the flow of people in the infected state into asymptomatic, pathologically infected but unconfirmed, and confirmed. |
Xinyu Wang; Lu Yang; Hong Zhang; Zhouwang Yang; Catherine Liu; | arxiv-stat.AP | 2020-12-01 |
| 260 | New Results On The Asymptotic Behavior Of An SIS Epidemiological Model With Quarantine Strategy, Stochastic Transmission, And Lévy Disturbance Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we analyze the impact of various stochastic disturbances on the epidemic dynamics during the quarantine period. |
Driss Kiouach; Yassine Sabbar; Salim El Azami El-idrissi; | arxiv-math.DS | 2020-12-01 |
| 261 | MAVIDH Score: A COVID-19 Severity Scoring Using Chest X-Ray Pathology Features IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Hence, a simple method based on lung-pathology interpretable features for scoring disease severity from Chest X-rays is proposed here. |
DOUGLAS P. S. GOMES et. al. | arxiv-eess.IV | 2020-11-30 |
| 262 | ViDi: Descriptive Visual Data Clustering As Radiologist Assistant In COVID-19 Streamline Diagnostic IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by descriptive document clustering, we propose a domain-independent explanatory clustering framework to group contextually related instances and support radiologists’ decision making. |
Sahithya Ravi; Samaneh Khoshrou; Mykola Pechenizkiy; | arxiv-eess.IV | 2020-11-30 |
| 263 | Modified Dorfman Procedure For Pool Tests With Dilution — COVID-19 Case Study IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose and analyze a simple modification of this procedure in which test of a pool with negative result is independently repeated up to several times. |
Andrzej Jaszkiewicz; | arxiv-stat.ME | 2020-11-30 |
| 264 | Seasonal Association Between Viral Causes of Hospitalised Acute Lower Respiratory Infections and Meteorological Factors in China: A Retrospective Study IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our aim was to identify the dominant meteorological factors and to model their effects on common respiratory viruses in different regions of China. |
BING XU et. al. | arxiv-stat.AP | 2020-11-30 |
| 265 | Exact Inference For Disease Prevalence Based On A Test With Unknown Specificity And Sensitivity IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we have proposed a set of 95% confidence intervals, whose validity is guaranteed and doesn’t depend on the sample size in the unweighted setting. |
Bryan Cai; John P. A. Ioannidis; Eran Bendavid; Lu Tian; | arxiv-stat.ME | 2020-11-29 |
| 266 | Clustering US States By Time Series of COVID-19 New Case Counts with Non-negative Matrix Factorization IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We proposed to cluster the US states into distinct communities based on the daily new confirmed case counts via a nonnegative matrix factorization (NMF) followed by a k-means clustering procedure on the coefficients of the NMF basis. |
Jianmin Chen; Jun Yan; Panpan Zhang; | arxiv-stat.AP | 2020-11-29 |
| 267 | Artificial Intelligence Applied To Chest X-Ray Images For The Automatic Detection Of COVID-19. A Thoughtful Evaluation Approach IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: With the long term goal to provide new evidence for the diagnosis, this paper presents an evaluation of different methods based on a deep neural network. |
Julian D. Arias-Londoño; Jorge A. Gomez-Garcia; Laureano Moro-Velazquez; Juan I. Godino-Llorente; | arxiv-eess.IV | 2020-11-28 |
| 268 | Contact Tracing Enhances The Efficiency Of COVID-19 Group Testing IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we use side information (SI) collected from contact tracing (CT) within non-adaptive/single-stage group testing algorithms. We generate data by incorporating CT SI and characteristics of disease spread between individuals. |
Ritesh Goenka; Shu-Jie Cao; Chau-Wai Wong; Ajit Rajwade; Dror Baron; | arxiv-stat.AP | 2020-11-28 |
| 269 | Fair And Diverse Allocation Of Scarce Resources IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We aim to design a fairness-aware allocation approach to maximize the geographical diversity and avoid unfairness in the sense of demographic disparity. |
Hadis Anahideh; Lulu Kang; Nazanin Nezami; | arxiv-math.OC | 2020-11-28 |
| 270 | Domain Adaptation Based COVID-19 CT Lung Infections Segmentation Network IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we use limited real data without annotations and a large amount of annotated synthetic data to train the U-Net segmentation network jointly. |
Han Chen; Yifan Jiang; Hanseok Ko; | arxiv-eess.IV | 2020-11-23 |
| 271 | Direct Transcription For Dynamic Optimization: A Tutorial With A Case Study On Dual-Patient Ventilation During The COVID-19 Pandemic IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper uses a unifying notation to outline some of the techniques used in the transcription step of simultaneous direct methods (which discretize-then-optimize) for solving continuous-time dynamic optimization problems. |
ERIC C. KERRIGAN et. al. | arxiv-math.OC | 2020-11-23 |
| 272 | Federated Semi-Supervised Learning For COVID Region Segmentation In Chest CT Using Multi-National Data From China, Italy, Japan IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we attempt to find a solution for this challenge via federated and semi-supervised learning. |
DONG YANG et. al. | arxiv-eess.IV | 2020-11-23 |
| 273 | Accurate and Rapid Diagnosis of COVID-19 Pneumonia with Batch Effect Removal of Chest CT-Scans and Interpretable Artificial Intelligence IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We trained and evaluated the model on a large dataset of 3359 samples from 6 different medical centers. |
RASSA GHAVAMI MODEGH et. al. | arxiv-eess.IV | 2020-11-23 |
| 274 | Explainable-by-design Semi-Supervised Representation Learning For COVID-19 Diagnosis From CT Imaging IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our motivating application is a real-world problem: COVID-19 classification from CT imaging, for which we present an explainable Deep Learning approach based on a semi-supervised classification pipeline that employs variational autoencoders to extract efficient feature embedding. |
ABEL DÍAZ BERENGUER et. al. | arxiv-eess.IV | 2020-11-23 |
| 275 | The Short-run Impact Of COVID-19 On The Activity In The Insurance Industry In The Republic Of North Macedonia IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper investigates the impact of the COVID-19 pandemic on the insurance industry in the Republic of North Macedonia during the first half of 2020. |
Viktor Stojkoski; Petar Jolakoski; Igor Ivanovski; | arxiv-q-fin.RM | 2020-11-21 |
| 276 | Quickest Detection of COVID-19 Pandemic Onset IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper develops an easily-implementable version of Page’s CUSUM quickest-detection test, designed to work in certain composite hypothesis scenarios with time-varying data statistics. |
PAOLO BRACA et. al. | arxiv-eess.SP | 2020-11-20 |
| 277 | Variational Bayes Method for ODE Parameter Estimation with Application to Time-varying SIR Model for COVID-19 Epidemic IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a Bayesian ODE parameter estimating algorithm which is fast and accurate even for models with many parameters. |
Hyunjoo Yang; Jaeyong Lee; | arxiv-stat.AP | 2020-11-19 |
| 278 | Positively Correlated Samples Save Pooled Testing Costs IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The other is to propose a hierarchical agglomerative algorithm for pooled testing with a social graph, where an edge in the social graph connects frequent social contacts between two persons. |
Yi-Jheng Lin; Che-Hao Yu; Tzu-Hsuan Liu; Cheng-Shang Chang; Wen-Tsuen Chen; | arxiv-stat.ME | 2020-11-19 |
| 279 | Targeted Self Supervision For Classification On A Small COVID-19 CT Scan Dataset IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The aim of this study is to determine whether self supervision can increase classification performance on a small COVID-19 CT scan dataset. |
Nicolas Ewen; Naimul Khan; | arxiv-eess.IV | 2020-11-19 |
| 280 | The Development And Deployment Of A Model For Hospital-level COVID-19 Associated Patient Demand Intervals From Consistent Estimators (DICE) IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce such a forecast, DICE (Demand Intervals from Consistent Estimators). |
Linying Yang; Teng Zhang; Peter Glynn; David Scheinker; | arxiv-stat.AP | 2020-11-18 |
| 281 | Estimating Seroprevalence Of SARS-CoV-2 In Ohio: A Bayesian Multilevel Poststratification Approach With Multiple Diagnostic Tests IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We describe a new Bayesian approach for analyzing the biomarker data that simultaneously addresses these challenges and characterizes the potential effect of selective response. |
DAVID KLINE et. al. | arxiv-stat.ME | 2020-11-17 |
| 282 | Decision And Feature Level Fusion Of Deep Features Extracted From Public COVID-19 Data-sets IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The aspects of the proposed method that are superior to existing COVID-19 detection studies have been discussed and the fusion performance of proposed approach was validated visually by using Class Activation Mapping technique. |
Hamza Osman Ilhan; Gorkem Serbes; Nizamettin Aydin; | arxiv-eess.IV | 2020-11-17 |
| 283 | Change Point Detection For COVID-19 Excess Deaths In Belgium IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We apply a change point detection method to identify any change points using the excess deaths in Belgium. |
Han Lin Shang; Ruofan Xu; | arxiv-stat.AP | 2020-11-16 |
| 284 | Group Design In Group Testing For COVID-19 : A French Case-study IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we address the problem of group testing design, which aims to determine a partition into groups of a finite population in such a way that cardinality constraints on the size of each group and a constraint on the expected total number of tests are satisfied while minimizing a linear combination of the expected number of false negative and false positive classifications. |
TIFAOUT ALMEFTAH et. al. | arxiv-stat.ME | 2020-11-13 |
| 285 | Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: More precisely, we show that linking voter roll data — containing individual-level voter turnout for specific voting locations along with race and age — can facilitate the construction of rigorous bias and reliability tests. |
AMANDA COSTON et. al. | arxiv-stat.AP | 2020-11-13 |
| 286 | Social Distancing And COVID-19: Randomization Inference For A Structured Dose-Response Relationship IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, we develop a design-based framework to make inference about the dose-response relationship between social distancing and COVID-19 related death toll and case numbers. |
Bo Zhang; Siyu Heng; Ting Ye; Dylan S. Small; | arxiv-stat.AP | 2020-11-12 |
| 287 | An Exploratory Assessment Of A Multidimensional Healthcare And Economic Data On COVID-19 In Nigeria IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This data article provides a dataset of daily updates of COVID-19 as reported online by the Nigeria Centre for Disease Control (NCDC) from February 27, 2020 to September 29, 2020. |
EZEKIEL OGUNDEPO et. al. | arxiv-stat.AP | 2020-11-12 |
| 288 | Shift Identification In Time Varying Regression Quantiles IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We formalise this issue in a corresponding non-parametric hypothesis testing problem, and develop a integrated-squared-norm based test (SIT) as well as a simultaneous confidence band (SCB) approach. |
Subhra Sankar Dhar; Weichi Wu; | arxiv-stat.ME | 2020-11-12 |
| 289 | A Trial Emulation Approach For Policy Evaluations With Group-level Longitudinal Data IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To limit the spread of the novel coronavirus, governments across the world implemented extraordinary physical distancing policies, such as stay-at-home orders, and numerous studies aim to estimate their effects. |
Eli Ben-Michael; Avi Feller; Elizabeth A. Stuart; | arxiv-stat.ME | 2020-11-11 |
| 290 | Multiscale Attention Guided Network for COVID-19 Diagnosis Using Chest X-ray Images IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our multiscale attention model achieves better classification performance on our pneumonia CXR image dataset. |
JINGXIONG LI et. al. | arxiv-eess.IV | 2020-11-11 |
| 291 | Classification Of COVID-19 In Chest CT Images Using Convolutional Support Vector Machines IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Methods: In this study, a deep learning model that detects COVID-19 cases with high performance is presented. |
Umut Özkaya; Şaban Öztürk; Serkan Budak; Farid Melgani; Kemal Polat; | arxiv-eess.IV | 2020-11-11 |
| 292 | Pristine Annotations-based Multi-modal Trained Artificial Intelligence Solution To Triage Chest X-ray For COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our proposed solution differs from existing solutions by industry and academic communities, and demonstrates a functional AI model to triage by inferencing using a single x-ray image, while the deep-learning model is trained using both X-ray and CT data. |
TAO TAN et. al. | arxiv-eess.IV | 2020-11-10 |
| 293 | Anomaly Detection Of Mobility Data With Applications To COVID-19 Situational Awareness IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work introduces a live anomaly detection system for high frequency and high-dimensional data collected at regional scale such as Origin Destination Matrices of mobile positioning data. |
Stefano Maria Iacus; Francesco Sermi; Spyridon Spyratos; Dario Tarchi; Michele Vespe; | arxiv-stat.AP | 2020-11-09 |
| 294 | Spatio-temporal Small Area Surveillance Of The Covid-19 Pandemics IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we propose a new spatio-temporal disease mapping model, particularly suited to Covid-19 surveillance. |
Miguel A. Martinez-Beneito; Jorge Mateu; Paloma Botella-Rocamora; | arxiv-stat.AP | 2020-11-08 |
| 295 | Inference Under Superspreading: Determinants Of SARS-CoV-2 Transmission In Germany IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: I propose a model for aggregated case data that accounts for superspreading and improves statistical inference. |
Patrick W. Schmidt; | arxiv-stat.AP | 2020-11-08 |
| 296 | Reel Stock Analysis For An Integrated Paper Packaging Company IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We provide a fresh approach to determining near-optimal stock policies for integrated paper companies. |
Constantine Goulimis; Gaston Simone; | arxiv-q-fin.GN | 2020-11-08 |
| 297 | Reducing Latency and Bandwidth for Video Streaming Using Keypoint Extraction and Digital Puppetry IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes an alternative to the conventional codec through the implementation of a keypoint-centric encoder relying on the transmission of keypoint information from within a video feed. |
ROSHAN PRABHAKAR et. al. | arxiv-eess.IV | 2020-11-07 |
| 298 | GP-LVM Of Categorical Data From Test-positive COVID-19 Pregnant Women IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we model categorical variables of 89 test-positive COVID-19 pregnant women within the unsupervised Bayesian framework. |
MARZIEH AJIRAK et. al. | arxiv-stat.AP | 2020-11-07 |
| 299 | Mid-Epidemic Forecasts Of COVID-19 Cases And Deaths: A Bivariate Model Applied To The UK IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here we focus on a practical forecasting approach, applied to interim UK COVID data, using a bivariate Reynolds model (cases and deaths). |
Peter Congdon; | arxiv-stat.AP | 2020-11-07 |
| 300 | Optimal Resource And Demand Redistribution For Healthcare Systems Under Stress From COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we study the problem of finding optimal demand and resource transfers to minimize the required surge capacity and resource shortage during a period of heightened demand. |
Felix Parker; Hamilton Sawczuk; Fardin Ganjkhanloo; Farzin Ahmadi; Kimia Ghobadi; | arxiv-math.OC | 2020-11-06 |
| 301 | Chest X-ray Image Phase Features for Improved Diagnosis of COVID-19 Using Convolutional Neural Network IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we design a novel multi-feature convolutional neural network (CNN) architecture for multi-class improved classification of COVID-19 from CXR images. |
Xiao Qi; Lloyd Brown; David J. Foran; Ilker Hacihaliloglu; | arxiv-eess.IV | 2020-11-06 |
| 302 | These Unprecedented Times: The Dynamic Pattern Of COVID-19 Deaths Around The World IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, we deal with COVID-19 data to study the trend of the epidemic at the global situation. |
Zixuan Han; Tao Li; Jinghong You; | arxiv-stat.AP | 2020-11-05 |
| 303 | Bayesian Inference Of Heterogeneous Epidemic Models: Application To COVID-19 Spread Accounting For Long-term Care Facilities IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a high dimensional Bayesian inference framework for learning heterogeneous dynamics of a COVID-19 model, with a specific application to the dynamics and severity of COVID-19 inside and outside long-term care (LTC) facilities. |
Peng Chen; Keyi Wu; Omar Ghattas; | arxiv-stat.ME | 2020-11-02 |
| 304 | On Control Of Epidemics With Application To COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: With this motivation in mind, in this paper, we consider a version of a stochastic discrete-time Susceptible-Infected-Recovered-Death~(SIRD)-based epidemiological model with two uncertainties: The uncertain rate of infected cases which are undetected or asymptomatic, and the uncertain effectiveness rate of control. |
Chung-Han Hsieh; | arxiv-math.OC | 2020-11-02 |
| 305 | How Much Testing And Social Distancing Is Required To Control COVID-19? Some Insight Based On An Age-differentiated Compartmental Model IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we provide insights on how much testing and social distancing is required to control COVID-19. |
SARA GRUNDEL et. al. | arxiv-math.OC | 2020-11-02 |
| 306 | Data-Driven Control Of The COVID-19 Outbreak Via Non-Pharmaceutical Interventions: A Geometric Programming Approach IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we propose a data-driven model for the spread of SARS-CoV-2 and use it to design optimal control strategies of human-mobility restrictions that both curb the epidemic and minimize the economic costs associated with implementing non-pharmaceutical interventions. We propose an optimal control problem on this data-driven model with a tractable solution provided by geometric programming. |
Mikhail Hayhoe; Francisco Barreras; Victor M. Preciado; | arxiv-math.OC | 2020-11-02 |
| 307 | Assessing Racial Inequality In COVID-19 Testing With Bayesian Threshold Tests IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: There are racial disparities in the COVID-19 test positivity rate, suggesting that minorities may be under-tested. Here, drawing on the literature on statistically assessing … |
Emma Pierson; | arxiv-stat.AP | 2020-11-02 |
| 308 | Mobile Human Ad Hoc Networks: A Communication Engineering Viewpoint On Interhuman Airborne Pathogen Transmission IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we propose a communication engineering approach that melts different disciplines such as epidemiology, biology, medicine, and fluid dynamics in the same pot to model airborne pathogen transmission among humans. |
Fatih Gulec; Baris Atakan; | arxiv-eess.SP | 2020-11-02 |
| 309 | Triage Of Potential COVID-19 Patients From Chest X-ray Images Using Hierarchical Convolutional Networks IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose the use of hierarchical convolutional network (HCN) architecture to naturally augment the data along with diversified features. |
Kapal Dev; Sunder Ali Khowaja; Ankur Singh Bist; Vaibhav Saini; Surbhi Bhatia; | arxiv-eess.IV | 2020-11-01 |
| 310 | Bifurcated Autoencoder For Segmentation Of COVID-19 Infected Regions In CT Images IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes an approach to segment lung regions infected by COVID-19 to help cardiologists diagnose the disease more accurately, faster, and more manageable. |
PARHAM YAZDEKHASTY et. al. | arxiv-eess.IV | 2020-11-01 |
| 311 | Optimal Minimal-contact Customer Routing Through Grocery Stores IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this context, we present an optimization framework for identifying routes through a grocery store that eliminate or minimize contacts between customers at grocery stock points while also minimizing the time spent within the store. |
Diptangshu Sen; Varun Ramamohan; Prasanna Ramamoorthy; | arxiv-math.OC | 2020-11-01 |
| 312 | Causal Inference For Spatial Treatments IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: I propose a framework, estimators, and inference procedures for the analysis of causal effects in a setting with spatial treatments. |
Michael Pollmann; | arxiv-econ.EM | 2020-10-31 |
| 313 | Infectious Disease Transmission Via Aerosol Propagation from A Molecular Communication Perspective: Shannon Meets Coronavirus IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this tutorial, aerosol and droplet transmission is modeled as a multiuser scenario with mobile nodes, related to broadcasting and relaying. |
MAX SCHURWANZ et. al. | arxiv-eess.SP | 2020-10-31 |
| 314 | Multi-stage Transfer Learning for Lung Segmentation Using Portable X-ray Devices for Patients with COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To solve this problem, we propose a methodology that allows to adapt the knowledge from a well-known domain with a high number of samples to a new domain with a significantly reduced number and greater complexity. |
Plácido L Vidal; Joaquim de Moura; Jorge Novo; Marcos Ortega; | arxiv-eess.IV | 2020-10-30 |
| 315 | Spatiotemporal Effects Of The Causal Factors On COVID-19 Incidences In The Contiguous United States IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, this study adopts various relevant approaches, including local and global spatial regression models and machine learning to explore the causal effects of the confounding factors on COVID-19 counts in the contiguous US. |
ARABINDA MAITI et. al. | arxiv-stat.AP | 2020-10-29 |
| 316 | COVID-19 Incidences And Its Association With Environmental Quality: A Country-level Assessment In India IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This study explored the association between the five key air pollutants (Nitrogen Dioxide (NO2), Sulphur Dioxide (SO2), Particulate Matter (PM2.5, PM10), and Carbon Monoxide (CO)) and COVID-19 incidences in India. |
Arabinda Maiti; Suman Chakraborti; Suvamoy Pramanik; Srikanta Sannigrahi; | arxiv-stat.AP | 2020-10-29 |
| 317 | FLANNEL: Focal Loss Based Neural Network Ensemble For COVID-19 Detection IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To identify COVID-19, we propose a Focal Loss Based Neural Ensemble Network (FLANNEL), a flexible module to ensemble several convolutional neural network (CNN) models and fuse with a focal loss for accurate COVID-19 detection on class imbalance data. We construct the X-ray imaging data from two publicly available sources, which include 5508 chest x-ray images across 2874 patients with four classes: normal, bacterial pneumonia, non-COVID-19 viral pneumonia, and COVID-19. |
Zhi Qiao; Austin Bae; Lucas M. Glass; Cao Xiao; Jimeng Sun; | arxiv-eess.IV | 2020-10-29 |
| 318 | CT-CAPS: Feature Extraction-based Automated Framework For COVID-19 Disease Identification From Chest CT Scans Using Capsule Networks IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, a Capsule network framework, referred to as the CT-CAPS, is presented to automatically extract distinctive features of chest CT scans. |
SHAHIN HEIDARIAN et. al. | arxiv-eess.IV | 2020-10-29 |
| 319 | COVID-FACT: A Fully-Automated Capsule Network-based Framework For Identification Of COVID-19 Cases From Chest CT Scans IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a two-stage fully-automated CT-based framework for identification of COVID-19 positive cases referred to as the COVID-FACT. |
SHAHIN HEIDARIAN et. al. | arxiv-eess.IV | 2020-10-29 |
| 320 | Modeling And Control Of COVID-19 Epidemic Through Testing Policies IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, an epidemic model that incorporates the testing rate as a control input is presented. |
MUHAMMAD UMAR B. NIAZI et. al. | arxiv-math.OC | 2020-10-29 |
| 321 | Multiscale Characteristics of The Emerging Global Cryptocurrency Market IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The review introduces the history of cryptocurrencies, offering a description of the blockchain technology behind them. |
MARCIN WĄTOREK et. al. | arxiv-q-fin.ST | 2020-10-29 |
| 322 | Prediction of Personal Protective Equipment Use in Hospitals During COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To meet this challenge, we propose an approach to predict demand for PPE. |
EUGENE FURMAN et. al. | arxiv-stat.AP | 2020-10-29 |
| 323 | A Statistical Model To Assess Risk For Supporting SARS-CoV-2 Quarantine Decisions IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This motivates our work in which we present a statistical model for the probability that no transmission of Sars-CoV-2 occurred given an arbitrary number of test results at potentially different timepoints. |
SONJA JÄCKLE et. al. | arxiv-stat.AP | 2020-10-29 |
| 324 | A Stochastic $θ$-SEIHRD Model: Adding Randomness To The COVID-19 Spread Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article we mainly extend the deterministic model developed in [10] to a stochastic setting. |
Álvaro Leitao; Carlos Vázquez; | arxiv-math.NA | 2020-10-29 |
| 325 | Space-Time Covid-19 Bayesian SIR Modeling In South Carolina IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The daily case and death data as reported by NCHS (deaths) via the New York Times GitHUB repository have been analyzed and approaches to modeling of the data are presented. |
Andrew B. Lawson; Joanne Kim; | arxiv-stat.AP | 2020-10-28 |
| 326 | Point Of Care Image Analysis For COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here we train deep neural networks to significantly enhance the capability to detect, grade and monitor COVID-19 patients using CXRs and LUS. Collaborating with several hospitals in Israel we collect a large dataset of CXRs and use this dataset to train a neural network obtaining above 90% detection rate for COVID-19. In addition, in collaboration with ULTRa (Ultrasound Laboratory Trento, Italy) and hospitals in Italy we obtained POC ultrasound data with annotations of the severity of disease and trained a deep network for automatic severity grading. |
DANIEL YARON et. al. | arxiv-eess.IV | 2020-10-28 |
| 327 | Triple-view Convolutional Neural Networks For COVID-19 Diagnosis With Chest X-ray IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address these issues, unlike traditional methods processing each CXR image from a single view, this paper proposes triple-view convolutional neural networks for COVID-19 diagnosis with CXR images. |
Jianjia Zhang; | arxiv-eess.IV | 2020-10-27 |
| 328 | Nonparametric Estimation Of Highest Density Regions For COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we compare the behavior of classical plug-in methods and a recently proposed hybrid algorithm for highest density regions estimation through an extensive simulation study. |
Paula Saavedra-Nieves; | arxiv-stat.ME | 2020-10-27 |
| 329 | Epidemic Dynamics Via Wavelet Theory And Machine Learning, With Applications To Covid-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a novel method for modelling epidemic dynamics by a model selection method using wavelet theory and, for its applications, machine learning based curve fitting techniques. |
TÔ TAT DAT et. al. | arxiv-math.OC | 2020-10-26 |
| 330 | A Simple But Efficient Concept of Blended Teaching of Mathematics for Engineering Students During The COVID-19 Pandemic IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a simple but efficient concept for the realization of blended teaching of mathematics and its applications in theoretical mechanics that was conceived, tested and implemented at the University of Trento, Italy, during the COVID-19 pandemic. |
Saray Busto; Michael Dumbser; Elena Gaburro; | arxiv-math.HO | 2020-10-26 |
| 331 | Interpreting Uncertainty In Model Predictions For COVID-19 Diagnosis IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This framework aims to understand the contribution of individual features in the Chest-X-Ray images to predictive uncertainty. |
Gayathiri Murugamoorthy; Naimul Khan; | arxiv-eess.IV | 2020-10-25 |
| 332 | Diverse R-PPG: Camera-Based Heart Rate Estimation For Diverse Subject Skin-Tones And Scenes IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a novel physics-driven algorithm that boosts performance on darker skin tones in our reported data. |
PRADYUMNA CHARI et. al. | arxiv-eess.IV | 2020-10-24 |
| 333 | Optimal Lockdown for Pandemic Control IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here we propose a mathematical framework of pandemic control through an optimal non-uniform lockdown, where our goal is to reduce the economic activity as little as possible while decreasing the number of infected individuals at a prescribed rate. |
Qianqian Ma; Yang-Yu Liu; Alex Olshevsky; | arxiv-math.OC | 2020-10-24 |
| 334 | Automated Triage Of COVID-19 From Various Lung Abnormalities Using Chest CT Features IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a fully automated AI based system that takes as input chest CT scans and triages COVID-19 cases. |
DOR AMRAN et. al. | arxiv-eess.IV | 2020-10-24 |
| 335 | Nowcasting COVID-19 Incidence Indicators During The Italian First Outbreak IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: A novel parametric regression model is proposed to fit incidence data typically collected during epidemics. |
PIERFRANCESCO ALAIMO DI LORO et. al. | arxiv-stat.AP | 2020-10-23 |
| 336 | Comparison Of ARIMA, ETS, NNAR And Hybrid Models To Forecast The Second Wave Of COVID-19 Hospitalizations In Italy IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, I analysed several time series forecasting methods to predict the spread of COVID-19 second wave in Italy, over the period after October 13, 2020. |
Gaetano Perone; | arxiv-stat.AP | 2020-10-22 |
| 337 | Robust Estimation of SARS-CoV-2 Epidemic in US Counties IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a robust approach to estimate the heterogeneous progression of SARS-CoV-2 at all US counties having no less than 2 COVID-19 associated deaths, and we use the daily probability of contracting (PoC) SARS-CoV-2 for a susceptible individual to quantify the risk of SARS-CoV-2 transmission in a community. |
Hanmo Li; Mengyang Gu; | arxiv-stat.AP | 2020-10-22 |
| 338 | Deep Learning For Distinguishing Normal Versus Abnormal Chest Radiographs And Generalization To Unseen Diseases IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we developed and evaluated an AI system to classify CXRs as normal or abnormal. |
ZAID NABULSI et. al. | arxiv-eess.IV | 2020-10-21 |
| 339 | Detection Of COVID-19 Through The Analysis Of Vocal Fold Oscillations IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our goal is to validate this hypothesis, and to quantitatively characterize the changes observed to enable the detection of COVID-19 from voice. |
Mahmoud Al Ismail; Soham Deshmukh; Rita Singh; | arxiv-eess.AS | 2020-10-20 |
| 340 | Excess Deaths, Baselines, Z-scores, P-scores And Peaks IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The data in the article is taken from these three sources. |
Laurie Davies; | arxiv-stat.AP | 2020-10-20 |
| 341 | Synthesis Of COVID-19 Chest X-rays Using Unpaired Image-to-Image Translation IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Motivated by the lack of publicly available datasets of chest radiographs of positive patients with Coronavirus disease 2019 (COVID-19), we build the first-of-its-kind open dataset of synthetic COVID-19 chest X-ray images of high fidelity using an unsupervised domain adaptation approach by leveraging class conditioning and adversarial training. |
Hasib Zunair; A. Ben Hamza; | arxiv-eess.IV | 2020-10-20 |
| 342 | GASNet: Weakly-supervised Framework For COVID-19 Lesion Segmentation IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a weakly-supervised lesion segmentation framework by embedding the Generative Adversarial training process into the Segmentation Network, which is called GASNet. |
ZHANWEI XU et. al. | arxiv-eess.IV | 2020-10-19 |
| 343 | Forecasting Unemployment Using Internet Search Data Via PRISM IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we present a novel method PRISM (Penalized Regression with Inferred Seasonality Module), which uses publicly available online search data from Google. |
Dingdong Yi; Shaoyang Ning; Chia-Jung Chang; S. C. Kou; | arxiv-stat.AP | 2020-10-19 |
| 344 | CT Image Segmentation for Inflamed and Fibrotic Lungs Using A Multi-Resolution Convolutional Neural Network IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The purpose of this study was to develop a fully-automated segmentation algorithm, robust to various density enhancing lung abnormalities, to facilitate rapid quantitative analysis of computed tomography images. |
SARAH E. GERARD et. al. | arxiv-eess.IV | 2020-10-16 |
| 345 | Minimax Quasi-Bayesian Estimation in Sparse Canonical Correlation Analysis Via A Rayleigh Quotient Function Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a quasi-Bayesian estimation procedure that achieves the minimax estimation rate, and yet is easy to compute by Markov Chain Monte Carlo (MCMC). |
Qiuyun Zhu; Yves Atchade; | arxiv-stat.ML | 2020-10-16 |
| 346 | Early-stage COVID-19 Diagnosis In Presence Of Limited Posteroanterior Chest X-ray Images Via Novel Pinball-OCSVM IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by this phenomenon, this article proposes a novel PB-OCSVM model to work in presence of limited COVID-19 positive CXR samples with objectives to maximize the learning efficiency while minimize the false-positive and false-negative predictions. |
Sanjay Kumar Sonbhadra; Sonali Agarwal; P. Nagabhushan; | arxiv-eess.IV | 2020-10-15 |
| 347 | Vehicular Networks For Combating A Worldwide Pandemic: Preventing The Spread Of COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This article provides an extensive discussion on vehicular networking for combating a pandemic. |
Ahmet M. Elbir; Gokhan Gurbilek; Burak Soner; Sinem Coleri; | arxiv-eess.SP | 2020-10-15 |
| 348 | Revisiting SIR In The Age Of COVID-19: Explicit Solutions And Control Problems IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The non-population conserving SIR (SIR-NC) model to describe the spread of infections in a community is proposed and studied. |
Vivek S. Borkar; D. Manjunath; | arxiv-math.OC | 2020-10-13 |
| 349 | Generalized Rescaled Polya Urn and Its Statistical Applications Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce the Generalized Rescaled Polya (GRP) urn, that provides a generative model for a chi-squared test of goodness of fit for the long-term probabilities of clustered data, with independence between clusters and correlation, due to a reinforcement mechanism, inside each cluster. |
Giacomo Aletti; Irene Crimaldi; | arxiv-math.ST | 2020-10-13 |
| 350 | Assessing Excess Mortality In Times Of Pandemics Based On Principal Component Analysis Of Weekly Mortality Data — The Case Of COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a blend of classical epidemiological approaches to estimating excess mortality during extraordinary events with an established demographic approach in mortality forecasting, namely a Lee-Carter type model, which covers the named limitations and draws a more realistic picture of the excess mortality. |
Patrizio Vanella; Ugofilippo Basellini; Berit Lange; | arxiv-stat.AP | 2020-10-10 |
| 351 | An Empirical Study On Detecting COVID-19 In Chest X-ray Images Using Deep Learning Based Methods IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we have studied the usage of x-ray pictures which are ubiquitous, for the classification of COVID-19 chest Xray images, by the existing convolutional neural networks (CNNs). |
Ramtin Babaeipour; Elham Azizi; Hassan Khotanlou; | arxiv-eess.IV | 2020-10-10 |
| 352 | Optimal Control Of Vaccination And Plasma Transfusion With Potential Usefulness For COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this chapter, we introduce two control functions in the compartmental SEIR model representing vaccination and plasma transfusion. |
Juliana Couras; Ivan Area; Juan J. Nieto; Cristiana J. Silva; Delfim F. M. Torres; | arxiv-math.OC | 2020-10-08 |
| 353 | Modeling The Commodity Prices Of Base Metals In Indian Commodity Market Using A Higher Order Markovian Approach IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: A Higher Order Markovian (HOM) model to capture the dynamics of commodity prices is proposed as an alternative to a Markovian model. In particular, the order of the former model, … |
Suryadeepto Nag; Sankarshan Basu; Siddhartha P. Chakrabarty; | arxiv-q-fin.TR | 2020-10-07 |
| 354 | M3Lung-Sys: A Deep Learning System For Multi-Class Lung Pneumonia Screening From CT Imaging IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Considering the limited training cases and resources (e.g, time and budget), we propose a Multi-task Multi-slice Deep Learning System (M3Lung-Sys) for multi-class lung pneumonia screening from CT imaging, which only consists of two 2D CNN networks, i.e., slice- and patient-level classification networks. |
XUELIN QIAN et. al. | arxiv-eess.IV | 2020-10-07 |
| 355 | No Increase In COVID-19 Mortality After The 2020 Primary Elections In The USA IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We examined the impact of voting on the spread of COVID-19 after the US primary elections held from March 17 to July 11, 2020 (1574 counties across 34 states). |
Eric M. Feltham; Laura Forastiere; Marcus Alexander; Nicholas A. Christakis; | arxiv-stat.AP | 2020-10-06 |
| 356 | Anomaly Detection Approach to Identify Early Cases in A Pandemic Using Chest X-rays IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To solve this problem, we present several unsupervised deep learning approaches, including convolutional and adversarially trained autoencoder. |
Shehroz S. Khan; Faraz Khoshbakhtian; Ahmed Bilal Ashraf; | arxiv-eess.IV | 2020-10-06 |
| 357 | Modeling Of Covid-19 Pandemic In Cyprus IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The aim of this paper is to present the efforts of this new, multidisciplinary research team in modelling the COVID-19 pandemic in the Republic of Cyprus. |
SERGIOS AGAPIOU et. al. | arxiv-stat.AP | 2020-10-05 |
| 358 | Forecasting COVID-19 Daily Cases Using Phone Call Data IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we propose a simple Multiple Linear Regression model, optimised to use call data to forecast the number of daily confirmed cases. |
Bahman Rostami-Tabar; Juan F. Rendon-Sanchez; | arxiv-stat.AP | 2020-10-05 |
| 359 | COVID-19 Classification Of X-ray Images Using Deep Neural Networks IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this retrospective study, a classifier was built using a pre-trained deep learning model (ReNet50) and enhanced by data augmentation and lung segmentation to detect COVID-19 in frontal CXR images collected between January 2018 and July 2020 in four hospitals in Israel. |
ELISHA GOLDSTEIN et. al. | arxiv-eess.IV | 2020-10-03 |
| 360 | Correlation Between Air And Urban Travelling With New Confirmed Cases Of COVID-19 A Case Study IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, the correlation between traveling between cities with new confirmed cases of COVID-19 in Iran is demonstrated. |
Soheil Shirvani; Anita Ghandehari; Hadi Moradi; | arxiv-stat.AP | 2020-10-03 |
| 361 | Commuting Network Spillovers and COVID-19 Deaths Across US Counties IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This study explored how population mobility flows form commuting networks across US counties and influence the spread of COVID-19. |
Christopher Seto; Aria Khademi; Corina Graif; Vasant G. Honavar; | arxiv-stat.AP | 2020-10-02 |
| 362 | Gold Standard Pairs Trading Rules: Are They Valid? IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We employ the most common distance and cointegration methods on US equities from 1990 to 2020 including the Covid-19 crisis. |
Miroslav Fil; | arxiv-q-fin.TR | 2020-10-02 |
| 363 | COVID-19, Economic Policy Uncertainty And Stock Market Crash Risk IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we use the GARCH-S (GARCH with skewness) model to estimate daily skewness as a proxy for the stock market crash risk. |
Zhifeng Liu; Toan Luu Duc Huynh; Jianjun Sun; Peng-Fei Dai; | arxiv-q-fin.GN | 2020-10-02 |
| 364 | Identification Of Images Of COVID-19 From Chest Computed Tomography (CT) Images Using Deep Learning: Comparing COGNEX VisionPro Deep Learning 1.0 Software With Open Source Convolutional Neural Networks IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we train the classification model on 82,818 chest CT training and validation images from the COVIDx-CT dataset in 3 classes – normal, pneumonia, and COVID-19 and then test the results of the classification on the 21,191 test images are compared with the results of COVIDNet-CT and various other state of the art Deep Learning models from the open-source community. |
Arjun Sarkar; Joerg Vandenhirtz; Jozsef Nagy; David Bacsa; Mitchell Riley; | arxiv-eess.IV | 2020-10-01 |
| 365 | Model-based Bayesian Inference Of Disease Outbreak Dynamics With Invertible Neural Networks IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: With this work, we introduce a novel coupling between epidemiological models and specialized neural network architectures. |
STEFAN T. RADEV et. al. | arxiv-stat.AP | 2020-10-01 |
| 366 | Modeling And Analysis Of The Effect Of COVID-19 On The Stock Price: V And L-shape Recovery IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We assume that during the crash, the stock price fall is independent of the $\phi$. |
Ajit Mahata; Anish rai; Om Prakash; Md Nurujjaman; | arxiv-q-fin.ST | 2020-09-28 |
| 367 | A Hierarchical Spatio-temporal Model To Analyze Relative Risk Variations Of COVID-19: A Focus On Spain, Italy And Germany IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we use a spatio-temporal stochastic model to explain the temporal and spatial variations in the daily number of new confirmed cases in Spain, Italy and Germany from late February to mid September 2020. |
Abdollah Jalilian; Jorge Mateu; | arxiv-stat.AP | 2020-09-28 |
| 368 | An Analysis of Network Filtering Methods to Sovereign Bond Yields During COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we investigate the impact of the COVID-19 pandemic on sovereign bond yields. |
Raymond Ka-Kay Pang; Oscar Granados; Harsh Chhajer; Erika Fille Legara; | arxiv-q-fin.ST | 2020-09-28 |
| 369 | COVID-19 Infection Map Generation and Detection from Chest X-Ray Images IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This study proposes a novel method for the joint localization, severity grading, and detection of COVID-19 from CXR images by generating the so-called infection maps. Furthermore, we publicly release the first CXR dataset with the ground-truth segmentation masks of the COVID-19 infected regions. |
AYSEN DEGERLI et. al. | arxiv-eess.IV | 2020-09-26 |
| 370 | Potential Features of ICU Admission in X-ray Images of COVID-19 Patients IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents an original methodology for extracting semantic features that correlate to severity from a data set with patient ICU admission labels through interpretable models. |
DOUGLAS P. S. GOMES et. al. | arxiv-eess.IV | 2020-09-26 |
| 371 | Estimation of The Incubation Time Distribution for COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We consider smooth nonparametric estimation of the incubation time distribution of COVID-19, in connection with the investigation of researchers from the National Institute for Public Health and the Environment (Dutch: RIVM) of 88 travelers from Wuhan: Backer et al (2020). |
Piet Groeneboom; | arxiv-stat.AP | 2020-09-26 |
| 372 | The Impact Of Modelling Choices On Modelling Outcomes: A Spatio-temporal Study Of The Association Between COVID-19 Spread And Environmental Conditions In Catalonia (Spain) IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, a COVID-19 dataset containing the number of daily cases registered in the regions of Catalonia (Spain) since the start of the pandemic is analysed. |
Álvaro Briz-Redón; | arxiv-stat.AP | 2020-09-26 |
| 373 | Deep Learning-based Four-region Lung Segmentation In Chest Radiography For COVID-19 Diagnosis IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address these, we proposed a four region lung segmentation method to assist accurate quantification of COVID 19 pneumonia. |
YOUNG-GON KIM et. al. | arxiv-eess.IV | 2020-09-26 |
| 374 | Efficient Calibration For Imperfect Epidemic Models With Applications To The Analysis Of COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: It is shown in this paper that this method is inefficient, particularly when the epidemic models are developed based on certain simplifications of reality, also known as imperfect models which are commonly used in practice. |
Chih-Li Sung; Ying Hung; | arxiv-stat.ME | 2020-09-26 |
| 375 | ECOVNet: An Ensemble Of Deep Convolutional Neural Networks Based On EfficientNet To Detect COVID-19 From Chest X-rays IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposed an ensemble of deep convolutional neural networks (CNN) based on EfficientNet, named ECOVNet, to detect COVID-19 using a large chest X-ray data set. |
Nihad Karim Chowdhury; Muhammad Ashad Kabir; Md. Muhtadir Rahman; Noortaz Rezoana; | arxiv-eess.IV | 2020-09-24 |
| 376 | An Elementary Approach For Minimax Estimation Of Bernoulli Proportion In The Restricted Parameter Space IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present an elementary mathematical method to find the minimax estimator of the Bernoulli proportion $\theta$ under the squared error loss when $\theta$ belongs to the restricted parameter space of the form $\Omega = [0, \eta]$ for some pre-specified constant $0 \leq \eta \leq 1$. |
Heejune Sheen; Yajun Mei; | arxiv-math.ST | 2020-09-23 |
| 377 | An Attention Mechanism With Multiple Knowledge Sources For COVID-19 Detection From CT Images IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: Until now, Coronavirus SARS-CoV-2 has caused more than 850,000 deaths and infected more than 27 million individuals in over 120 countries. Besides principal polymerase chain … |
DUY M. H. NGUYEN et. al. | arxiv-eess.IV | 2020-09-23 |
| 378 | Classification Of COVID-19 In CT Scans Using Multi-Source Transfer Learning IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we propose the use of Multi-Source Transfer Learning (MSTL) to improve upon traditional Transfer Learning for the classification of COVID-19 from CT scans. |
Alejandro R. Martinez; | arxiv-eess.IV | 2020-09-22 |
| 379 | CCBlock: An Effective Use Of Deep Learning For Automatic Diagnosis Of COVID-19 Using X-Ray Images IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Materials and Methods: Based on the enhancement of the classical visual geometry group (VGG) network with the convolutional COVID block (CCBlock), an efficient screening model was proposed in this study to diagnose and distinguish patients with the COVID-19 from those with pneumonia and the healthy people through radiography. |
Ali Al-Bawi; Karrar Ali Al-Kaabi; Mohammed Jeryo; Ahmad Al-Fatlawi; | arxiv-eess.IV | 2020-09-21 |
| 380 | Improving Automated COVID-19 Grading With Convolutional Neural Networks In Computed Tomography Scans: An Ablation Study IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Amidst the ongoing pandemic, several studies have shown that COVID-19 classification and grading using computed tomography (CT) images can be automated with convolutional neural networks (CNNs). |
COEN DE VENTE et. al. | arxiv-eess.IV | 2020-09-21 |
| 381 | Impact of Lung Segmentation on The Diagnosis and Explanation of COVID-19 in Chest X-ray Images IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This study aims to demonstrate the impact of lung segmentation in COVID-19 identification using CXR images and evaluate which contents of the image decisively contribute to its identification. |
LUCAS O. TEIXEIRA et. al. | arxiv-eess.IV | 2020-09-21 |
| 382 | A Relationship Between SIR Model And Generalized Logistic Distribution With Applications To SARS And COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper shows that the generalized logistic distribution model is derived from the well-known compartment model, consisting of susceptible, infected and recovered compartments, abbreviated as the SIR model, under certain conditions. |
Hideo Hirose; | arxiv-stat.AP | 2020-09-21 |
| 383 | Complexity In Economic And Social Systems: Cryptocurrency Market At Around COVID-19 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We approach this subject from all three perspectives based on data recorded between January 2019 and June 2020. |
Stanisław Drożdż; Jarosław Kwapień; Paweł Oświęcimka; Tomasz Stanisz; Marcin Wątorek; | arxiv-q-fin.ST | 2020-09-21 |
| 384 | Bias Field Poses A Threat to DNN-based X-Ray Recognition IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we study this problem based on the recent adversarial attack and propose a brand new attack, i.e., the adversarial bias field attack where the bias field instead of the additive noise works as the adversarial perturbations for fooling the DNNs. |
BINYU TIAN et. al. | arxiv-eess.IV | 2020-09-19 |
| 385 | Epidemiological Forecasting With Model Reduction Of Compartmental Models. Application To The COVID-19 Pandemic IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a forecasting method for predicting epidemiological health series on a two-week horizon at the regional and interregional resolution. |
Athmane Bakhta; Thomas Boiveau; Yvon Maday; Olga Mula; | arxiv-stat.ME | 2020-09-19 |
| 386 | Estimating The Treatment Effect Of The Juvenile Stay-at-home Order On SARS-CoV-2 Infection Spread In Saline County, Arkansas IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We investigate the treatment effect of the juvenile stay-at-home order (JSAHO) adopted in Saline County, Arkansas, from April 6 to May 7, in mitigating the growth of SARS-CoV-2 infection rates. |
Neil Hwang; Shirshendu Chatterjee; Yanming Di; Sharmodeep Bhattacharyya; | arxiv-stat.AP | 2020-09-18 |
| 387 | Functional Data Analysis: An Application To COVID-19 Data In The United States IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we use methods from the functional data analysis to look into the COVID-19 data in the US. |
Chen Tang; Tiandong Wang; Panpan Zhang; | arxiv-stat.AP | 2020-09-17 |
| 388 | Variational Disentanglement For Rare Event Modeling IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: So motivated, we propose a variational disentanglement approach to semi-parametrically learn from rare events in heavily imbalanced classification problems. |
ZIDI XIU et. al. | arxiv-stat.ML | 2020-09-17 |
| 389 | Detection Of Change Points In Piecewise Polynomial Signals Using Trend Filtering IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a change point detection method, PRUTF, based on trend filtering. |
Reza V. Mehrizi; Shojaeddin Chenouri; | arxiv-stat.ME | 2020-09-17 |
| 390 | Fears For COVID-19: The Crash Risk Of Stock Market IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper investigates the impact of COVID-19 epidemic on the Chinese stock market crash risk. |
Zhifeng Liu; Toan Luu Duc Huynh; Peng-Fei Dai; | arxiv-q-fin.GN | 2020-09-16 |
| 391 | High-resolution Spatio-temporal Model for County-level COVID-19 Activity in The U.S IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present an interpretable high-resolution spatio-temporal model to estimate COVID-19 deaths together with confirmed cases one-week ahead of the current time, at the county-level and weekly aggregated, in the United States. |
SHIXIANG ZHU et. al. | arxiv-stat.AP | 2020-09-15 |
| 392 | Adaptive Methods For Short-Term Electricity Load Forecasting During COVID-19 Lockdown In France IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we introduce adaptive generalized additive models using Kalman filters and fine-tuning to adjust to new electricity consumption patterns. |
David Obst; Joseph de Vilmarest; Yannig Goude; | arxiv-stat.AP | 2020-09-14 |
| 393 | Time-varying Auto-regressive Models for Count Time-series Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose two Bayesian models, a time-varying semiparametric AR(p) model for count and then a time-varying INGARCH model considering the rapid changes in the spread. |
Arkaprava Roy; Sayar Karmakar; | arxiv-stat.ME | 2020-09-13 |
| 394 | Tracking Disease Outbreaks From Sparse Data With Bayesian Inference IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a Bayesian framework which accommodates partial observability in a principled manner. |
Bryan Wilder; Michael J. Mina; Milind Tambe; | arxiv-stat.ME | 2020-09-12 |
| 395 | Bayesian Beta-Binomial Prevalence Estimation Using An Imperfect Test IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: An efficient Monte Carlo algorithm for approximating the posterior density is presented, and applied to estimating the Covid-19 infection rate in Santa Clara county, CA using the data reported in [Bendavid 2020]. |
Jonathan Baxter; | arxiv-stat.AP | 2020-09-11 |
| 396 | Covid-19 Impact On Cryptocurrencies: Evidence From A Wavelet-based Hurst Exponent IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our study covers the pre-Covid-19 and the subsequent pandemia period. |
M. Belén Arouxet; Aurelio F. Bariviera; Verónica E. Pastor; Victoria Vampa; | arxiv-q-fin.ST | 2020-09-11 |
| 397 | Dual Encoder Fusion U-Net (DEFU-Net) For Cross-manufacturer Chest X-ray Segmentation IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a dual encoder fusion U-Net framework for Chest X-rays based on Inception Convolutional Neural Network with dilation, Densely Connected Recurrent Convolutional Neural Network, which is named DEFU-Net. |
Lipei Zhang; Aozhi Liu; Jing Xiao; Paul Taylor; | arxiv-eess.IV | 2020-09-11 |
| 398 | Probabilistic And Mean-field Model Of COVID-19 Epidemics With User Mobility And Contact Tracing IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a detailed discrete-time model of COVID-19 epidemics coming in two flavours, mean-field and probabilistic. |
M. Akian; L. Ganassali; S. Gaubert; L. Massoulié; | arxiv-stat.AP | 2020-09-11 |
| 399 | COVID CT-Net: Predicting Covid-19 From Chest CT Images Using Attentional Convolutional Network IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we developed a deep learning framework to predict COVID-19 from CT images. |
Shakib Yazdani; Shervin Minaee; Rahele Kafieh; Narges Saeedizadeh; Milan Sonka; | arxiv-eess.IV | 2020-09-10 |
| 400 | Comprehensive Comparison of Deep Learning Models for Lung and COVID-19 Lesion Segmentation in CT Scans IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, an extensive comparison of DL models for lung and COVID-19 lesion segmentation in Computerized Tomography (CT) scans is presented, which can also be used as a benchmark for testing medical image segmentation models. |
Paschalis Bizopoulos; Nicholas Vretos; Petros Daras; | arxiv-eess.IV | 2020-09-10 |
| 401 | Forecasting Financial Markets With Semantic Network Analysis In The COVID-19 Crisis IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper uses a new textual data index for predicting stock market data. |
A. Fronzetti Colladon; S. Grassi; F. Ravazzolo; F. Violante; | arxiv-q-fin.GN | 2020-09-09 |
| 402 | Referenced Thermodynamic Integration for Bayesian Model Selection: Application to COVID-19 Model Selection IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we apply a variation of the TI method, referred to as referenced TI, which computes a single model’s normalising constant in an efficient way by using a judiciously chosen reference density. |
Iwona Hawryluk; Swapnil Mishra; Seth Flaxman; Samir Bhatt; Thomas A. Mellan; | arxiv-stat.AP | 2020-09-08 |
| 403 | Spatial Bayesian Hierarchical Modelling With Integrated Nested Laplace Approximation IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We consider latent Gaussian fields for modelling spatial dependence in the context of both spatial point patterns and areal data, providing two different applications. |
Nicoletta D’Angelo; Antonino Abbruzzo; Giada Adelfio; | arxiv-stat.AP | 2020-09-08 |
| 404 | Label-Free Segmentation of COVID-19 Lesions in Lung CT IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To alleviate the burden of data annotation, we herein present a label-free approach for segmenting COVID-19 lesions in CT via pixel-level anomaly modeling that mines out the relevant knowledge from normal CT lung scans. |
Qingsong Yao; Li Xiao; Peihang Liu; S. Kevin Zhou; | arxiv-eess.IV | 2020-09-08 |
| 405 | Fuzzy Unique Image Transformation: Defense Against Adversarial Attacks On Deep COVID-19 Models IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents an evaluation of the performance of deep COVID-19 models against adversarial attacks. |
Achyut Mani Tripathi; Ashish Mishra; | arxiv-eess.IV | 2020-09-08 |
| 406 | Information: To Harvest, To Have And To Hold IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We here propose novel metrics to assess the amount of information harvested in an experiment, information which is measured in bits. |
Marin van Heel; Michael Schatz; | arxiv-eess.IV | 2020-09-07 |
| 407 | Anomaly Detection In Stationary Settings: A Permutation-Based Higher Criticism Approach IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we take a non-parametric stance, and propose a permutation-based variant of the higher criticism statistic not requiring knowledge of the null distribution. |
Ivo V. Stoepker; Rui M. Castro; Ery Arias-Castro; Edwin van den Heuvel; | arxiv-stat.ME | 2020-09-07 |
| 408 | Optimization Of High-dimensional Simulation Models Using Synthetic Data IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce the BuB simulator, which requires only the specification of plausible intervals for the simulation parameters. |
Thomas Bartz-Beielstein; Eva Bartz; Frederik Rehbach; Olaf Mersmann; | arxiv-stat.AP | 2020-09-06 |
| 409 | Using Multiple Data Streams To Estimate And Forecast SARS-CoV-2 Transmission Dynamics, With Application To The Virus Spread In Orange County, California IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To overcome this obstacle, at least partially, we propose a Bayesian modeling framework that integrates multiple surveillance data streams. |
JONATHAN FINTZI et. al. | arxiv-stat.AP | 2020-09-06 |
| 410 | COVID-19: Tail Risk and Predictive Regressions IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper focuses on econometrically justified robust analysis of the effects of the COVID-19 pandemic on the World’s financial markets in different countries across the World. |
Walter Distaso; Rustam Ibragimov; Alexander Semenov; Anton Skrobotov; | arxiv-econ.EM | 2020-09-05 |
| 411 | Brownian Snails With Removal: Pandemics In A Diffusing Population IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: A stochastic model of susceptible/infected/removed (SIR) type, inspired by COVID-19, is introduced for the spread of infection through a spatially-distributed population. |
Geoffrey R. Grimmett; Zhongyang Li; | arxiv-math.PR | 2020-09-05 |
| 412 | Adaptive Preferential Sampling In Phylodynamics IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce an approach where the sampling process is modeled as an inhomogeneous Poisson process with rate equal to the product of $N_{e}(t)$ and a time-varying coefficient, making minimal assumptions on their functional shapes via Markov random field priors. |
Lorenzo Cappello; Julia A. Palacios; | arxiv-stat.AP | 2020-09-04 |
| 413 | Proximity Sensing: Modeling And Understanding Noisy RSSI-BLE Signals And Other Mobile Sensor Data For Digital Contact Tracing IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To enable efficient digital contact tracing, we present a novel system to estimate pair-wise individual proximity, via a joint model of Bluetooth Low Energy (BLE) signals with other on-device sensors (accelerometer, magnetometer, gyroscope). |
SHESHANK SHANKAR et. al. | arxiv-eess.SP | 2020-09-03 |
| 414 | COVID-19 Policy Impact Evaluation: A Guide to Common Design Issues IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we (1) introduce the basic suite of policy impact evaluation designs for observational data, including cross-sectional analyses, pre/post, interrupted time-series, and difference-in-differences analysis, (2) demonstrate key ways in which the requirements and assumptions underlying these designs are often violated in the context of COVID-19, and (3) provide decision-makers and reviewers a conceptual and graphical guide to identifying these key violations. |
Noah A Haber; Emma Clarke-Deelder; Joshua A Salomon; Avi Feller; Elizabeth A Stuart; | arxiv-stat.ME | 2020-09-03 |
| 415 | Estimating The Reciprocal Of A Binomial Proportion IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by this, we propose to further advance the literature by developing an optimal estimator for the inverse proportion in a family of shrinkage estimators. |
Jiajin Wei; Ping He; Tiejun Tong; | arxiv-stat.ME | 2020-09-02 |
| 416 | Covid 19 And A Wavelet Analysis Of The Total Deaths Per Month In Brazil Since 2015 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We investigate the historical series of the total number of deaths per month in Brazil since 2015 using the wavelet transform, in order to assess whether the COVID-19 pandemic caused any change point in that series. |
Alexandre Barbosa de Lima; | arxiv-eess.SP | 2020-09-01 |
| 417 | The Battle Of Infinity: Explosive Demand Surge Vs Gigantic Service Providers IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We provide a new stability criterion based on the Borel-Cantelli lemma to judge whether the infinite server safely accommodates heavy-tailed demands. |
Hiroshi Toyoizumi; | arxiv-math.PR | 2020-08-31 |
| 418 | Real-time Prediction Of COVID-19 Related Mortality Using Electronic Health Records IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here, we present the COVID-19 Early Warning System (CovEWS), a clinical risk scoring system for assessing COVID-19 related mortality risk. |
PATRICK SCHWAB et. al. | arxiv-stat.AP | 2020-08-31 |
| 419 | Nowcasting In A Pandemic Using Non-Parametric Mixed Frequency VARs IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper develops Bayesian econometric methods for posterior inference in non-parametric mixed frequency VARs using additive regression trees. |
Florian Huber; Gary Koop; Luca Onorante; Michael Pfarrhofer; Josef Schreiner; | arxiv-econ.EM | 2020-08-28 |
| 420 | What Can We Learn From The Travelers Data In Detecting Disease Outbreaks — A Case Study Of The COVID-19 Epidemic IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We discussed how the traveler case reports could aid in a timely detection of a disease outbreak. |
Le Bao; Ying Zhang; Xiaoyue Niu; | arxiv-stat.AP | 2020-08-26 |
| 421 | On The Composition And Limitations Of Publicly Available COVID-19 X-Ray Imaging Datasets IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents an overview of the currently public available COVID-19 chest X-ray datasets. |
Beatriz Garcia Santa Cruz; Jan Sölter; Matias Nicolas Bossa; Andreas Dominik Husch; | arxiv-eess.IV | 2020-08-26 |
| 422 | DRR4Covid: Learning Automated COVID-19 Infection Segmentation From Digitally Reconstructed Radiographs IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a novel approach, called DRR4Covid, to learn automated COVID-19 diagnosis and infection segmentation on CXRs from digitally reconstructed radiographs (DRRs). |
Pengyi Zhang; Yunxin Zhong; Yulin Deng; Xiaoying Tang; Xiaoqiong Li; | arxiv-eess.IV | 2020-08-26 |
| 423 | Share Price Prediction Of Aerospace Relevant Companies With Recurrent Neural Networks Based On PCA IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To improve the prediction of share price for aerospace industry sector and well understand the impact of various indicators on stock prices, we provided a hybrid prediction model by the combination of Principal Component Analysis (PCA) and Recurrent Neural Networks. |
Linyu Zheng; Hongmei He; | arxiv-q-fin.ST | 2020-08-26 |
| 424 | An Exploratory Time Series Analysis Of Total Deaths Per Month In Brazil Since 2015 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, we investigate the historical series of the total number of deaths per month in Brazil since 2015 using time series analysis techniques, in order to assess whether the COVID-19 pandemic caused any change in the series’ generating mechanism. |
Alexandre Barbosa de Lima; | arxiv-stat.AP | 2020-08-26 |
| 425 | Quantifying The Impact Of COVID-19 On The US Stock Market: An Analysis From Multi-source Information IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We develop a novel temporal complex network approach to quantify the US county level spread dynamics of COVID-19. |
Asim Kumer Dey; Toufiqul Haq; Kumer Das; Irina Panovska; | arxiv-q-fin.ST | 2020-08-25 |
| 426 | Feedback Control of The COVID-19 Pandemic with Guaranteed Non-exceeding ICU Capacity IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we investigate feedback control techniques for the COVID-19 pandemic which are able to guarantee that the capacity of available intensive care unit beds is not exceeded. |
Thomas Berger; | arxiv-math.OC | 2020-08-21 |
| 427 | Comparative Performance Analysis Of The ResNet Backbones Of Mask RCNN To Segment The Signs Of COVID-19 In Chest CT Scans IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper aims to identify and monitor the effects of COVID-19 on the human lungs by employing Deep Neural Networks on axial CT (Chest Computed Tomography) scan of lungs. |
Muhammad Aleem; Rahul Raj; Arshad Khan; | arxiv-eess.IV | 2020-08-21 |
| 428 | Image Quality Assessment for Closed-loop Computer-assisted Lung Ultrasound IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We describe a novel, two-stage computer assistance system for lung anomaly detection using ultrasound imaging in the intensive care setting to improve operator performance and patient stratification during coronavirus pandemics. |
ZACHARY M C BAUM et. al. | arxiv-eess.IV | 2020-08-20 |
| 429 | Effect Of COVID-19 On Noise Pollution Change In Dublin, Ireland IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This study investigates noise pollution in Dublin, Ireland before and after the lockdown imposed as a result of the COVID-19 pandemic. |
BIDROHA BASU et. al. | arxiv-stat.AP | 2020-08-20 |
| 430 | The Smart Mask: Active Closed-Loop Protection Against Airborne Pathogens IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a new active mask paradigm, in which the wearable device is equipped with smart sensors and actuators to both detect the presence of airborne pathogens in real time and take appropriate action to mitigate the threat. |
NAREN VIKRAM RAJ MASNA et. al. | arxiv-eess.SP | 2020-08-20 |
| 431 | Spatial Homogeneity Learning For Spatially Correlated Functional Data With Application To COVID-19 Growth Rate Curves IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a geographically detailed functional data grouping method equipped with a functional conditional autoregressive (CAR) prior to fully capture the spatial correlation in the pandemic curves. |
Tianyu Pan; Weining Shen; Guanyu Hu; | arxiv-stat.AP | 2020-08-20 |
| 432 | Bear Markets And Recessions Versus Bull Markets And Expansions IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper examines the dynamic interaction between falling and rising markets for both the real and the financial sectors of the largest economy in the world using asymmetric causality tests. |
Abdulnasser Hatemi-J; | arxiv-q-fin.GN | 2020-08-20 |
| 433 | Correcting Data Imbalance For Semi-Supervised Covid-19 Detection Using X-ray Chest Images IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This is often a limitation when the subject of research is relatively new as in the case of the virus outbreak, where dealing with small labelled datasets is a challenge. |
SAUL CALDERON-RAMIREZ et. al. | arxiv-eess.IV | 2020-08-19 |
| 434 | Estimating The Effective Reproduction Number And Variables Of Disease Models For The COVID-19 Epidemic IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In order to overcome these shortcomings a constrained estimation method is proposed that keeps the model variables within pre-specified boundaries and can also promote smoothness of the estimates. |
Mauricio C. de Oliveira; | arxiv-math.OC | 2020-08-18 |
| 435 | Do Face Masks Introduce Bias In Speech Technologies? The Case Of Automated Scoring Of Speaking Proficiency IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we explore the impact of wearing face masks on the automated assessment of English language proficiency. |
Anastassia Loukina; Keelan Evanini; Matthew Mulholland; Ian Blood; Klaus Zechner; | arxiv-eess.AS | 2020-08-17 |
| 436 | A Real-time Robot-based Auxiliary System For Risk Evaluation Of COVID-19 Infection IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a real-time robot-based auxiliary system for risk evaluation of COVID-19 infection. |
Wenqi Wei; Jianzong Wang; Jiteng Ma; Ning Cheng; Jing Xiao; | arxiv-eess.AS | 2020-08-17 |
| 437 | Short Term Stress Of Covid-19 On World Major Stock Indices IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The main objective of this study is to check short term stress of COVID-19 on the American, European, Asian, and Pacific stock market indices, furthermore, the correlation between all the stock markets during the pandemic. |
Muhammad Rehan; Jahanzaib Alvi; Suleyman Serdar Karaca; | arxiv-q-fin.GN | 2020-08-14 |
| 438 | MIXCAPS: A Capsule Network-based Mixture Of Experts For Lung Nodule Malignancy Prediction IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Capitalizing on their success, in this study, we propose a novel capsule network-based mixture of experts, referred to as the MIXCAPS. |
PARNIAN AFSHAR et. al. | arxiv-eess.IV | 2020-08-13 |
| 439 | Spectral Processing Of COVID-19 Time-Series Data IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: The presence of oscillations in aggregated COVID-19 data not only raises questions about the data’s accuracy, it hinders understanding of the pandemic. Spectral analysis is used … |
Stephen McGovern; | arxiv-eess.SP | 2020-08-13 |
| 440 | Risk Measures Estimation Under Wasserstein Barycenter IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a new approach for modeling multivariate risk measures under Wasserstein barycenters of probability measures supported on location-scatter families. |
M. Andrea Arias-Serna; Jean-Michel Loubes; Francisco J. Caro-Lopera; | arxiv-stat.AP | 2020-08-13 |
| 441 | Bounding Infection Prevalence By Bounding Selectivity and Accuracy of Tests: With Application to Early COVID-19 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: I propose novel partial identification bounds on infection prevalence from information on test rate and test yield. |
Jörg Stoye; | arxiv-econ.EM | 2020-08-13 |
| 442 | Sensitivity Analysis Of Error-Contaminated Time Series Data Under Autoregressive Models With Application Of COVID-19 Data IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose two measurement error models to describe different processes of data contamination. |
Qihuang Zhang; Grace Y. Yi; | arxiv-stat.ME | 2020-08-12 |
| 443 | The Shapes Of An Epidemic: Using Functional Data Analysis To Characterize COVID-19 In Italy IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The techniques we describe could capture additional and potentially sharper signals if applied to richer data. |
Tobia Boschi; Jacopo Di Iorio; Lorenzo Testa; Marzia A. Cremona; Francesca Chiaromonte; | arxiv-stat.AP | 2020-08-11 |
| 444 | Time Fused Coefficient SIR Model with Application to COVID-19 Epidemic in The United States IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a Susceptible-Infected-Removal (SIR) model with time fused coefficients. |
Hou-Cheng Yang; Yishu Xue; Yuqing Pan; Qingyang Liu; Guanyu Hu; | arxiv-stat.AP | 2020-08-10 |
| 445 | Individualized Prediction Of COVID-19 Adverse Outcomes With MLHO IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We broadly describe the clusters of features that were utilized in modeling and their relative influence on predicting each outcome. |
Hossein Estiri; Zachary H. Strasser; Shawn N. Murphy; | arxiv-stat.ML | 2020-08-09 |
| 446 | Generalized K-Means In GLMs With Applications To The Outbreak Of COVID-19 In The United States IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: By choosing the dissimilarity measure as the well known likelihood ratio or $F$-statistic, this work proposes a method based on generalized $k$-means to group statistical models. |
Tonglin Zhang; Ge Lin; | arxiv-stat.ME | 2020-08-09 |
| 447 | On The Interplay of Regional Mobility, Social Connectedness, and The Spread of COVID-19 in Germany IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we, therefore, explore the impact of human mobility and social connectivity derived from Facebook activities on the weekly rate of new infections in Germany between March 3rd and June 22nd, 2020. |
Cornelius Fritz; Göran Kauermann; | arxiv-stat.AP | 2020-08-07 |
| 448 | COVID-19 Mortality Analysis from Soft-data Multivariate Curve Regression and Machine Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: A multiple objective space-time forecasting approach is presented involving cyclical curve log-regression, and multivariate time series spatial residual correlation analysis. |
A. Torres-Signes; M. P. Frías; M. D. Ruiz-Medina; | arxiv-stat.ML | 2020-08-07 |
| 449 | Teaching Economics With Interactive Browser-Based Models IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Interactive simulation toolkits come in handy when teaching macroeconomic models by facilitating an easy understanding of underlying economic concepts and offering an intuitive approach to the models’ comparative statics. |
Juan Dominguez-Moran; Rouven Geismar; | arxiv-q-fin.GN | 2020-08-06 |
| 450 | Spatiotemporal Dynamic Of COVID-19 Mortality In The City Of Sao Paulo, Brazil: Shifting The High Risk From The Best To The Worst Socio-economic Conditions IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We describe mortality rates for each epidemiological week and the entire period by sex and age. |
PATRICIA MARQUES MORALEJO BERMUDI et. al. | arxiv-stat.AP | 2020-08-05 |
| 451 | A Note On Tools For Prediction Under Uncertainty And Identifiability Of SIR-like Dynamical Systems For Epidemiology IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We provide an overview of the methods that can be used for prediction under uncertainty and data fitting of dynamical systems, and of the fundamental challenges that arise in this context. |
Chiara Piazzola; Lorenzo Tamellini; Raúl Tempone; | arxiv-stat.ME | 2020-08-04 |
| 452 | COVID-19 in CXR: from Detection and Severity Scoring to Patient Disease Monitoring Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we estimate the severity of pneumonia in COVID-19 patients and conduct a longitudinal study of disease progression. |
Rula Amer; Maayan Frid-Adar; Ophir Gozes; Jannette Nassar; Hayit Greenspan; | arxiv-eess.IV | 2020-08-04 |
| 453 | Robust Optimal Estimation of Location from Discretely Sampled Functional Data IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To remedy these deficiencies we introduce the first class of optimal robust location estimators based on discretely sampled functional data. |
Ioannis Kalogridis; Stefan Van Aelst; | arxiv-stat.ME | 2020-08-03 |
| 454 | Identification Of Images Of COVID-19 From Chest X-rays Using Deep Learning: Comparing COGNEX VisionPro Deep Learning 1.0 Software With Open Source Convolutional Neural Networks IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, COGNEXs Deep Learning Software-VisionPro Deep Learning is used to classify these Chest X-rays from the COVIDx dataset. |
Arjun Sarkar; Joerg Vandenhirtz; Jozsef Nagy; David Bacsa; Mitchell Riley; | arxiv-eess.IV | 2020-08-02 |
| 455 | Vector Quantisation And Partitioning Of COVID-19 Temporal Dynamics In The United States IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper outlines an analysis of time series vector quantisation and paritioning of COVID-19 cases in the United States, using a soft-DTW (Dynamic Time Warping) k-means clustering and a k-shape based clustering algorithm to identify internally consistent clusters of case counts over time. |
Chris von Csefalvay; | arxiv-stat.AP | 2020-08-02 |
| 456 | Contact Classification In COVID-19 Tracing IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our analysis identifies parameters that result in accurate warnings, at least within the scope of validity of the models. |
Christoph Günther; Daniel Günther; | arxiv-eess.SP | 2020-08-02 |
| 457 | Markovian And Non-Markovian Processes With Active Decision Making Strategies For Addressing The COVID-19 Pandemic IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We study and predict the evolution of Covid-19 in six US states from the period May 1 through August 31 using a discrete compartment-based model and prescribe active intervention policies, like lockdowns, on the basis of minimizing a loss function, within the broad framework of partially observed Markov decision processes. |
Hamid Eftekhari; Debarghya Mukherjee; Moulinath Banerjee; Ya’acov Ritov; | arxiv-stat.AP | 2020-08-01 |
| 458 | Estimating The Real Burden Of Disease Under A Pandemic Situation: The SARS-CoV2 Case IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The present paper introduces a new model used to study and analyse the severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) epidemic-reported-data from Spain. |
Amanda Fernández-Fontelo; David Moriña; Alejandra Cabaña; Argimiro Arratia; Pere Puig; | arxiv-stat.ME | 2020-08-01 |
| 459 | What Can We Learn About SARS-CoV-2 Prevalence from Testing and Hospital Data? IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We provide and test conditions under which this non-COVID hospitalization bound is valid for the general population. |
Daniel W. Sacks; Nir Menachemi; Peter Embi; Coady Wing; | arxiv-econ.EM | 2020-08-01 |
| 460 | Causal Inference Methods For Small Non-randomized Studies: Methods And An Application In COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Motivated by a non-randomized open-label study investigating the efficacy of hydroxychloroquine in patients with COVID-19, we describe in a unified fashion various alternative approaches to the analysis of non-randomized studies. |
Sarah Friedrich; Tim Friede; | arxiv-stat.AP | 2020-07-31 |
| 461 | Nonparametric Comparison Of Epidemic Time Trends: The Case Of COVID-19 IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we devise new inference methods that allow to detect differences in the development of the COVID-19 epidemic across countries in a statistically rigorous way. |
Marina Khismatullina; Michael Vogt; | arxiv-stat.ME | 2020-07-31 |
| 462 | Deep Direct Likelihood Knockoffs IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Predictive modeling often uses black box machine learning methods, such as deep neural networks, to achieve state-of-the-art performance. |
Mukund Sudarshan; Wesley Tansey; Rajesh Ranganath; | arxiv-stat.ML | 2020-07-31 |
| 463 | Regional Now- and Forecasting for Data Reported with Delay: Towards Surveillance of COVID-19 Infections Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We apply our model to German data, for which our focus lies in predicting and explain infectious behavior by district. |
Giacomo De Nicola; Marc Schneble; Göran Kauermann; Ursula Berger; | arxiv-stat.AP | 2020-07-31 |
| 464 | Equilibrium Oil Market Share Under The COVID-19 Pandemic IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We describe the uncertainties in the demand and supply by random variables and provide two types of production decisions (here-and-now and wait-and-see). |
Xiaojun Chen; Yun Shi; Xiaozhou Wang; | arxiv-math.OC | 2020-07-30 |
| 465 | Measuring The Effectiveness Of US Monetary Policy During The COVID-19 Recession IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To measure these effects at high frequencies, we propose a novel mixed frequency vector autoregressive (MF-VAR) model. |
Martin Feldkircher; Florian Huber; Michael Pfarrhofer; | arxiv-econ.EM | 2020-07-30 |
| 466 | COVID-19 CT Image Synthesis With A Conditional Generative Adversarial Network IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In order to meet the data requirements for COVID-19 CT imaging, we propose a CT image synthesis approach based on a conditional generative adversarial network that can effectively generate high-quality and realistic COVID-19 CT images for use in deep-learning-based medical imaging tasks. |
Yifan Jiang; Han Chen; Murray Loew; Hanseok Ko; | arxiv-eess.IV | 2020-07-29 |
| 467 | PDCOVIDNet: A Parallel-Dilated Convolutional Neural Network Architecture For Detecting COVID-19 From Chest X-Ray Images IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we proposed a parallel-dilated convolutional neural network (CNN) based COVID-19 detection system from chest x-ray images, named as Parallel-Dilated COVIDNet (PDCOVIDNet). |
Nihad Karim Chowdhury; Md. Muhtadir Rahman; Muhammad Ashad Kabir; | arxiv-eess.IV | 2020-07-29 |
| 468 | Comparative Study Of Deep Learning Methods For The Automatic Segmentation Of Lung, Lesion And Lesion Type In CT Scans Of COVID-19 Patients IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we compare twelve deep learning algorithms using a multi-center dataset, including both open-source and in-house developed algorithms. |
SOFIE TILBORGHS et. al. | arxiv-eess.IV | 2020-07-29 |
| 469 | Detecting Change Signs with Differential MDL Change Statistics for COVID-19 Pandemic Analysis Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a novel methodology to address this issue. |
Kenji Yamanishi; Linchuan Xu; Ryo Yuki; Shintaro Fukushima; Chuan-hao Lin; | arxiv-stat.AP | 2020-07-29 |
| 470 | CovMUNET: A Multiple Loss Approach Towards Detection Of COVID-19 From Chest X-ray IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose CovMUNET, which is a multiple loss deep neural network approach to detect COVID-19 cases from CXR images. |
A. Q. M. Sazzad Sayyed; Dipayan Saha; Abdul Rakib Hossain; | arxiv-eess.IV | 2020-07-28 |
| 471 | Parameter Estimation in Dynamical Systems Via Statistical Learning: A Reinterpretation of Approximate Bayesian Computation Applied to COVID-19 Spread Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a robust parameter estimation method for dynamical systems based on Statistical Learning techniques which aims to estimate a set of parameters that well fit the dynamics in order to obtain robust evidences about the qualitative behaviour of its trajectory. |
Diego Marcondes; | arxiv-stat.ME | 2020-07-28 |
| 472 | A Bayesian Hierarchical Network For Combining Heterogeneous Data Sources In Medical Diagnoses IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Motivated by a concrete application in antibody testing, we devise a Stochastic Expectation-Maximization algorithm that allows the principled integration of heterogeneous, and potentially unreliable, data types. |
Claire Donnat; Nina Miolane; Freddy Bunbury; Jack Kreindler; | arxiv-stat.AP | 2020-07-27 |
| 473 | How Robust Are The Estimated Effects Of Nonpharmaceutical Interventions Against COVID-19? IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To answer this question, we investigate 2 state-of-the-art NPI effectiveness models and propose 6 variants that make different structural assumptions. |
MRINANK SHARMA et. al. | arxiv-stat.AP | 2020-07-27 |
| 474 | Optimal Control of COVID-19 Infection Rate Considering Social Costs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We analyze how these strategies change when we incorporate vaccination into the model and find a new optimal `delay-mitigation’ strategy. |
Aaron Z. Palmer; Zelda B. Zabinsky; Shan Liu; | arxiv-math.OC | 2020-07-27 |
| 475 | The Causality Inference Of Public Interest In Restaurants And Bars On COVID-19 Daily Cases In The US: A Google Trends Analysis IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The objective of this study was to consider the predictive ability of different search terms (i.e., bars and restaurants) with regards to the increase of daily cases in the US. |
Milad Asgari Mehrabadi; Nikil Dutt; Amir M. Rahmani; | arxiv-stat.AP | 2020-07-26 |
| 476 | Study Of Different Deep Learning Approach With Explainable AI For Screening Patients With COVID-19 Symptoms: Using CT Scan And Chest X-ray Image Dataset IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Some studies proposed CT scan or chest X-ray images as an alternative solution. |
MD MANJURUL AHSAN et. al. | arxiv-eess.IV | 2020-07-24 |
| 477 | Causal Analysis Of Covid-19 Spread In Germany IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we study the causal relations among German regions in terms of the spread of Covid-19 since the beginning of the pandemic, taking into account the restriction policies that were applied by the different federal states. |
Atalanti A. Mastakouri; Bernhard Schölkopf; | arxiv-stat.AP | 2020-07-23 |
| 478 | COVID TV-UNet: Segmenting COVID-19 Chest CT Images Using Connectivity Imposed U-Net IF:2 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we propose a segmentation framework to detect chest regions in CT images, which are infected by COVID-19. |
Narges Saeedizadeh; Shervin Minaee; Rahele Kafieh; Shakib Yazdani; Milan Sonka; | arxiv-eess.IV | 2020-07-23 |
| 479 | Darwin’s Neural Network: AI-based Strategies For Rapid And Scalable Cell And Coronavirus Screening IF:2 Related Papers Related Patents Related Grants |