Development and clinical deployment of a smartphone-based visual field deep learning system for glaucoma detection

By 2040, ~100 million people will have glaucoma. To date, there are a lack of high-efficiency glaucoma diagnostic tools based on visual fields (VFs). Herein, we develop and evaluate the performance of ‘iGlaucoma’, a smartphone application-based deep learning system (DLS) in detecting glaucomatous VF...

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Detalles Bibliográficos
Autores principales: Li, Fei, Song, Diping, Chen, Han, Xiong, Jian, Li, Xingyi, Zhong, Hua, Tang, Guangxian, Fan, Sujie, Lam, Dennis S. C., Pan, Weihua, Zheng, Yajuan, Li, Ying, Qu, Guoxiang, He, Junjun, Wang, Zhe, Jin, Ling, Zhou, Rouxi, Song, Yunhe, Sun, Yi, Cheng, Weijing, Yang, Chunman, Fan, Yazhi, Li, Yingjie, Zhang, Hengli, Yuan, Ye, Xu, Yang, Xiong, Yunfan, Jin, Lingfei, Lv, Aiguo, Niu, Lingzhi, Liu, Yuhong, Li, Shaoli, Zhang, Jiani, Zangwill, Linda M., Frangi, Alejandro F., Aung, Tin, Cheng, Ching-yu, Qiao, Yu, Zhang, Xiulan, Ting, Daniel S. W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7508974/
https://www.ncbi.nlm.nih.gov/pubmed/33043147
http://dx.doi.org/10.1038/s41746-020-00329-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7508974/
https://www.ncbi.nlm.nih.gov/pubmed/33043147
http://dx.doi.org/10.1038/s41746-020-00329-9

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