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DeepSeeNet: A deep learning model for automated classification of patient-based age-related macular degeneration severity from color fundus photographs.

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A deep learning-based survival model for prediction of progression in late Age-related Macular Degeneration (AMD) from color fundus photographs., , , , , , and . AMIA, AMIA, (2019)Predicting risk of late age-related macular degeneration using deep learning., , , , , , , and . npj Digit. Medicine, (2020)A multi-task deep learning model for the classification of Age-related Macular Degeneration., , , , , , , and . CoRR, (2018)Detection of reticular pseudodrusen using deep learning., , , , , , , , , and . AMIA, AMIA, (2020)A deep learning approach for automated detection of geographic atrophy from color fundus photographs., , , , , , , and . CoRR, (2019)DeepSeeNet: A deep learning model for automated classification of patient-based age-related macular degeneration severity from color fundus photographs., , , , , , , and . CoRR, (2018)Predicting myocardial infarction through retinal scans and minimal personal information., , , , , , , , , and 7 other author(s). Nat. Mach. Intell., 4 (1): 55-61 (2022)Multimodal, multitask, multiattention (M3) deep learning detection of reticular pseudodrusen: Toward automated and accessible classification of age-related macular degeneration., , , , , , , , , and 7 other author(s). J. Am. Medical Informatics Assoc., 28 (6): 1135-1148 (2021)Multi-modal, multi-task, multi-attention (M3) deep learning detection of reticular pseudodrusen: towards automated and accessible classification of age-related macular degeneration., , , , , , , , , and 7 other author(s). CoRR, (2020)Deep learning automated diagnosis and quantitative classification of cataract type and severity: quantifying the effectiveness and usability of deep learning-assisted disease diagnosis models with 14 ophthalmologists and multi-center validations., , , , , and . AMIA, AMIA, (2022)