Performance of Deep Learning Architectures and Transfer Learning for Detecting Glaucomatous Optic Neuropathy in Fundus Photographs

The ability of deep learning architectures to identify glaucomatous optic neuropathy (GON) in fundus photographs was evaluated. A large database of fundus photographs (n = 14,822) from a racially and ethnically diverse group of individuals (over 33% of African descent) was evaluated by expert review...

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Detalles Bibliográficos
Autores principales: Christopher, Mark, Belghith, Akram, Bowd, Christopher, Proudfoot, James A., Goldbaum, Michael H., Weinreb, Robert N., Girkin, Christopher A., Liebmann, Jeffrey M., Zangwill, Linda M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6232132/
https://www.ncbi.nlm.nih.gov/pubmed/30420630
http://dx.doi.org/10.1038/s41598-018-35044-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6232132/
https://www.ncbi.nlm.nih.gov/pubmed/30420630
http://dx.doi.org/10.1038/s41598-018-35044-9

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