Non-invasive and accurate risk evaluation of cerebrovascular disease using retinal fundus photo based on deep learning

Non-invasive and accurate risk evaluation of cerebrovascular disease using retinal fundus photo based on deep learning

BackgroundCerebrovascular disease (CeVD) is a prominent contributor to global mortality and profound disability. Extensive research has unveiled a connection between CeVD and retinal microvascular abnormalities. Nonetheless, manual analysis of fundus images remains a laborious and time-consuming tas...

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Bibliographic Details
Main Authors: Lin An, Jia Qin, Weili Jiang, Penghao Luo, Xiaoyan Luo, Yuzheng Lai, Mei Jin
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-09-01
Series:Frontiers in Neurology
Subjects:
deep learning
cerebrovascular disease
stroke
artificial intelligence
attention
Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2023.1257388/full

Internet

https://www.frontiersin.org/articles/10.3389/fneur.2023.1257388/full

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