Development of a deep residual learning algorithm to screen for glaucoma from fundus photography

The Purpose of the study was to develop a deep residual learning algorithm to screen for glaucoma from fundus photography and measure its diagnostic performance compared to Residents in Ophthalmology. A training dataset consisted of 1,364 color fundus photographs with glaucomatous indications and 1,...

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Detalles Bibliográficos
Autores principales: Shibata, Naoto, Tanito, Masaki, Mitsuhashi, Keita, Fujino, Yuri, Matsuura, Masato, Murata, Hiroshi, Asaoka, Ryo
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/PMC6168579/
https://www.ncbi.nlm.nih.gov/pubmed/30279554
http://dx.doi.org/10.1038/s41598-018-33013-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6168579/
https://www.ncbi.nlm.nih.gov/pubmed/30279554
http://dx.doi.org/10.1038/s41598-018-33013-w

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