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

BACKGROUND: Deep 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 onse...

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Detalles Bibliográficos
Autores principales: Li, Fei, Su, Yuandong, Lin, Fengbin, Li, Zhihuan, Song, Yunhe, Nie, Sheng, Xu, Jie, Chen, Linjiang, Chen, Shiyan, Li, Hao, Xue, Kanmin, Che, Huixin, Chen, Zhengui, Yang, Bin, Zhang, Huiying, Ge, Ming, Zhong, Weihui, Yang, Chunman, Chen, Lina, Wang, Fanyin, Jia, Yunqin, Li, Wanlin, Wu, Yuqing, Li, Yingjie, Gao, Yuanxu, Zhou, Yong, Zhang, Kang, Zhang, Xiulan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Clinical Investigation 2022
Materias:
Clinical Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9151694/
https://www.ncbi.nlm.nih.gov/pubmed/35642636
http://dx.doi.org/10.1172/JCI157968

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9151694/
https://www.ncbi.nlm.nih.gov/pubmed/35642636
http://dx.doi.org/10.1172/JCI157968

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