A deep-learning system predicts glaucoma incidence and progression using retinal photographs.

BackgroundDeep learning has been widely used for glaucoma diagnosis. However, there is no clinically validated algorithm for glaucoma incidence and progression prediction. This study aims to develop a clinically feasible deep-learning system for predicting and stratifying the risk of glaucoma onset...

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Detalles Bibliográficos
Publicado en:Journal of Clinical Investigation Vol. 132; no. 11; pp. 1 - 11
Autores principales: Fei Li, Yuandong Su, Fengbin Lin, Zhihuan Li, Yunhe Song, Sheng Nie, Jie Xu, Linjiang Chen, Shiyan Chen, Hao Li, Kanmin Xue, Huixin Che, Zhengui Chen, Bin Yang, Huiying Zhang, Ming Ge, Weihui Zhong, Chunman Yang, Lina Chen, Fanyin Wang
Formato: research Journal Article
Publicado: American Society for Clinical Investigation 6/1/2022
Acceso en línea:Ver este registro en EBSCOhost