1. Deep Learning to Detect OCT-derived Diabetic Macular Edema from Color Retinal Photographs

    Deep Learning to Detect OCT-derived Diabetic Macular Edema from Color Retinal Photographs

    Purpose To validate the generalizability of a deep learning system (DLS) that detects diabetic macular edema (DME) from 2-dimensional color fundus photographs (CFP), for which the reference standard for retinal thickness and fluid presence is derived from 3-dimensional OCT. Design Retrospective validation of a DLS across international datasets. Participants Paired CFP and OCT of patients from diabetic retinopathy (DR) screening programs or retina clinics. The DLS was developed using data sets from Thailand, the United Kingdom, and the United States and validated using 3060 unique eyes from 1582 patients across screening populations in Australia, India, and Thailand. The DLS was ...

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