Hemoglobin Easy Measurement With Optical Artificial Intelligence

NCT04573244 — Completed, 823 participants, MYOR Ltd.

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A Prospective Feasibility Study to Explore the Utility of Using a Smartphone Camera to Monitor Blood Hemoglobin Levels in Children and Adolescents

Registry	NCT04573244, acronym HEMO-AI
Status	Completed
Study type	Observational
Enrollment	823 (Actual)
Sponsor	MYOR Ltd. (Industry)
Conditions	Hemoglobin; Deficiency
Dates	start 2020-12-02, primary completion 2023-08-31, completion 2023-08-31, first posted 2020-10-05, last updated 2024-08-23
Locations	1 site in Israel

-Summary

Blood hemoglobin levels are an extremely important measure for a large swath of medical procedures as they reflect the oxygen-carrying capacity of human blood. The gold standard measure for blood hemoglobin levels involve a venous blood draw followed by a laboratory-based complete blood count (CBC), a process which is both painful and time consuming. To date, various methodologies have been tested to either expediate the process or provide a non-invasive alternative. There remains a need to provide a quick, pain-free/non-invasive and accurate modality to measure blood hemoglobin levels. The objective of this study is to determine whether computer vision technologies can be applied to fingernail images captured via a smartphone camera to quantify blood hemoglobin levels.

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+Outcome measures

Primary outcomes

To determine whether computational learning methods can be applied to fingernail images captured via a smartphone camera to quantify blood hemoglobin levels. [6 months]: Evaluated using the hemoglobin portion of a conventional complete blood count (CBC)

Secondary outcomes

To determine whether computational learning methods can be applied to fingernail images captured via a smartphone camera to screen for anemia as defined by the WHO [6 months]: Evaluated using the hemoglobin portion of a conventional complete blood count (CBC). Anemia cutoff for children aged 6 months to 6 years = 11 g/dL and for children aged 6-14 years = 12 g/dL.
To determine whether computational learning methods can be applied to fingernail images captured via a smartphone camera to quantify other elements of the CBC [6 months]: Evaluated using the hemoglobin portion of a conventional complete blood count (CBC)

+Eligibility

Sex: All, ages: 6 Months to 18 Years, accepts healthy volunteers

Inclusion Criteria:

1. A patient aged 6 months to 18 years.
2. A patient who has undergone a venous blood draw for a CBC since being admitted to the PED no more than 6 hours prior to study enrollment.
3. Parents or legal guardian provide informed written consent.

Exclusion Criteria:

1. Patient has subungual hematoma, nail bed lacerations or avulsion injuries on both hands.
2. Patient has total leukonychia.
3. Patient has nail polish applied on fingernails.
4. Patient has nailbed darkening or discoloration due to medication.
5. Any other reason that, in the opinion of the investigator, prevents the subject from participating in the study or compromise the patient safety.

+Locations (1)

Facility	City	Country	Status
Emek Medical Center	Afula	Israel

+Publications

Results publication: Gordon D, Hoffman J, Gamrasni K, Barlev Y, Levine A, Landau T, Shpiegel R, Lahad A, Koren A, Levin C, Naor O, Lee H, Liu X, Patel S, Chayen G, Brandwein M. Artificial intelligence-enabled non-invasive ubiquitous anemia screening: The HEMO-AI pilot study on pediatric population. Digit Health. 2024 Dec 5;10:20552076241297057. doi: 10.1177/20552076241297057. eCollection 2024 Jan-Dec. PMID 39640961

+Investigators

Gilad Moshe Chayen, MD, Principal investigator, Emek Medical Center

My Notes

Public

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