Gender Prediction for a Multiethnic Population via Deep Learning Across Different Retinal Fundus Photograph Fields: Retrospective Cross-sectional Study

Gender Prediction for a Multiethnic Population via Deep Learning Across Different Retinal Fundus Photograph Fields: Retrospective Cross-sectional Study

BackgroundDeep learning algorithms have been built for the detection of systemic and eye diseases based on fundus photographs. The retina possesses features that can be affected by gender differences, and the extent to which these features are captured via photography differs...

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Bibliographic Details
Main Authors: Bjorn Kaijun Betzler, Henrik Hee Seung Yang, Sahil Thakur, Marco Yu, Ten Cheer Quek, Zhi Da Soh, Geunyoung Lee, Yih-Chung Tham, Tien Yin Wong, Tyler Hyungtaek Rim, Ching-Yu Cheng
Format: Article
Language:English
Published: JMIR Publications 2021-08-01
Series:JMIR Medical Informatics
Online Access:https://medinform.jmir.org/2021/8/e25165

Internet

https://medinform.jmir.org/2021/8/e25165

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