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

10.2196/25165

Saved in:
Bibliographic Details
Main Authors: Betzler, Bjorn Kaijun, Yang, Henrik Hee Seung, Thakur, Sahil, Yu, Marco, Quek, Ten Cheer, Da Soh, Zhi, Lee, Geunyoung, Tham, Yih-Chung, Wong, Tien Yin, Rim, Tyler Hyungtaek, Cheng, Ching-Yu
Other Authors: OPHTHALMOLOGY
Format: Review
Published: JMIR Publications Inc. 2022
Subjects:
Artificial intelligence
Deep learning
Gender
Ophthalmology
Retina
Online Access:https://scholarbank.nus.edu.sg/handle/10635/232429
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: National University of Singapore
Description
Summary:10.2196/25165

Similar Items