A deep learning model for novel systemic biomarkers in photographs of the external eye: a retrospective study.

ABSTRACT:

Background

Photographs of the external eye were recently shown to reveal signs of diabetic retinal disease and elevated glycated haemoglobin. This study aimed to test the hypothesis that external eye photographs contain information about additional systemic medical conditions.

Methods

We developed a deep learning system (DLS) that takes external eye photographs as input and predicts systemic parameters, such as those related to the liver (albumin, aspartate aminotransferase [AST]); kidney (estimated glomerular filtration rate [eGFR], urine albumin-to-creatinine ratio [ACR]); bone or mineral (calcium); thyroid (thyroid stimulating hormone); and blood (haemoglobin, white blood cells [WBC], platelets). This DLS was trained using 123 130 images from 38 398 patients with diabetes

SUBMITTER: Babenko B 

PROVIDER: S-EPMC11818944 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature