Predicting sex from retinal fundus photographs using automated deep learning

Deep learning may transform health care, but model development has largely been dependent on availability of advanced technical expertise. Herein we present the development of a deep learning model by clinicians without coding, which predicts reported sex from retinal fundus photographs. A model was...

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Detalles Bibliográficos
Autores principales: Korot, Edward, Pontikos, Nikolas, Liu, Xiaoxuan, Wagner, Siegfried K., Faes, Livia, Huemer, Josef, Balaskas, Konstantinos, Denniston, Alastair K., Khawaja, Anthony, Keane, Pearse A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8119673/
https://www.ncbi.nlm.nih.gov/pubmed/33986429
http://dx.doi.org/10.1038/s41598-021-89743-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8119673/
https://www.ncbi.nlm.nih.gov/pubmed/33986429
http://dx.doi.org/10.1038/s41598-021-89743-x

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