Prediction of hypertension, hyperglycemia and dyslipidemia from retinal fundus photographs via deep learning: A cross-sectional study of chronic diseases in central China

Retinal fundus photography provides a non-invasive approach for identifying early microcirculatory alterations of chronic diseases prior to the onset of overt clinical complications. Here, we developed neural network models to predict hypertension, hyperglycemia, dyslipidemia, and a range of risk fa...

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Detalles Bibliográficos
Autores principales: Zhang, Li, Yuan, Mengya, An, Zhen, Zhao, Xiangmei, Wu, Hui, Li, Haibin, Wang, Ya, Sun, Beibei, Li, Huijun, Ding, Shibin, Zeng, Xiang, Chao, Ling, Li, Pan, Wu, Weidong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7224473/
https://www.ncbi.nlm.nih.gov/pubmed/32407418
http://dx.doi.org/10.1371/journal.pone.0233166

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7224473/
https://www.ncbi.nlm.nih.gov/pubmed/32407418
http://dx.doi.org/10.1371/journal.pone.0233166

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