Applications of Fairness Training in Artificial Intelligence to Ophthalmic Disease Diagnosis using External Eye Photographs

Diabetic retinopathy (DR), age-related macular degeneration (AMD), and glaucoma are leading causes of preventable blindness, yet whether external eye photographs carry phenotypic information about posterior segment disease remains unclear, and methods to mitigate demographic disparities in such models are largely unexplored. We developed and evaluated deep learning and vision-language models for binary classification of vision-threatening DR (VTDR), advanced AMD, and glaucoma using 40,687 external eye photographs from 9,878 patients at Massachusetts Eye and Ear. Convolutional networks (WResNet

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