Deep learning approach for diabetic retinopathy screening

By E. Colás, A. Besse, A. Orgogozo, B. Schmauch, N. Meriç, E. Besse. 2016

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Interpretable and Fine-Grained Visual Explanations for Convolutional Neural Networks (2019, background): “Background of the disease: As people with diabetes have a high prevalence for RDR [47], a frequent retinal screening is recommended and deep learning algorithms have been successfully developed to classify fundus images ([8], [20], [3], [46]).”
Weakly-supervised localization of diabetic retinopathy lesions in retinal fundus images (2017, background): “While first approaches using neural networks to detect diabetic retinopathy on retinal images without additional feature extraction showed a low classification accuracy [5, 6], recent approaches based on deep neural networks [7, 8, 9] report good performance.”