Fairer AI in Ophthalmology via Implicit Fairness Learning for Mitigating Sexism and Ageism
Version 1We collect the largest and most diverse fundus image dataset with data from over 8,405 patients representing a wide age range (0 to 90 years). The fundus dataset contains two types of advanced ultra-widefield and regular narrow-angle fundus images, with the ultra-widefield imaging dataset containing 16,530 fundus images annotated with 38 ophthalmic diseases and 67 fundus features and the narrow-angle imaging dataset containing 4,540 fundus images annotated with 16 ophthalmic diseases and 20 fund
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We collect the largest and most diverse fundus image dataset with data from over 8,405 patients representing a wide age range (0 to 90 years). The fundus dataset contains two types of advanced ultra-widefield and regular narrow-angle fundus images, with the ultra-widefield imaging dataset containing 16,530 fundus images annotated with 38 ophthalmic diseases and 67 fundus features and the narrow-angle imaging dataset containing 4,540 fundus images annotated with 16 ophthalmic diseases and 20 fund