CORRECTION article
Front. Cell Dev. Biol.
Sec. Molecular and Cellular Pathology
Correction: Diagnostic performance and generalizability of deep learning for multiple retinal diseases using bimodal imaging of fundus photography and optical coherence tomography
Jingyuan Yang 1
Xingwang Gu 1
Yang Zhou 2
Jianchun Zhao 2
Hongzhe Zhang 1
Xinlei Pan 3
Bing Li 1
Bilei Zhang 4
Yuelin Wang 5
Song Xia 6
Hailan Lin 7
Jie Wang 7
Dayong Ding 2
Xirong Li 7
Shan Wu 8
Youxin Chen 1
1. Peking Union Medical College Hospital (CAMS), Beijing, China
2. Visionary Intelligence Ltd., Beijing, China
3. The First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
4. Hunan Provincial People's Hospital, Changsha, China
5. Peking University Third Hospital, Beijing, China
6. Guizhou Provincial People's Hospital, Guiyang, China
7. Renmin University of China, Beijing, China
8. Beijing Hospital, Beijing, China
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Summary
Keywords
deep learning, diagnosis, fundus photography, Optical Coherence Tomography, Retinal disease
Received
18 February 2026
Accepted
19 February 2026
Copyright
© 2026 Yang, Gu, Zhou, Zhao, Zhang, Pan, Li, Zhang, Wang, Xia, Lin, Wang, Ding, Li, Wu and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Jingyuan Yang
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.