Age and sex affect deep learning prediction of cardiometabolic risk factors from retinal images

Deep neural networks can extract clinical information, such as diabetic retinopathy status and individual characteristics (e.g. age and sex), from retinal images. Here, we report the first study to train deep learning models with retinal images from 3,000 Qatari citizens participating in the Qatar B...

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Detalles Bibliográficos
Autores principales: Gerrits, Nele, Elen, Bart, Craenendonck, Toon Van, Triantafyllidou, Danai, Petropoulos, Ioannis N., Malik, Rayaz A., Boever, Patrick De
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/PMC7287116/
https://www.ncbi.nlm.nih.gov/pubmed/32523046
http://dx.doi.org/10.1038/s41598-020-65794-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7287116/
https://www.ncbi.nlm.nih.gov/pubmed/32523046
http://dx.doi.org/10.1038/s41598-020-65794-4

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