Automated program using convolutional neural networks for objective and reproducible selection of corneal confocal microscopy images
The algorithm is open source and compatible with standard CCM workflows, offering researchers and clinicians a robust and efficient tool for DPN diagnosis. Further, multicentre studies are needed to validate these findings in diverse populations.
Authors
- Yongkai Yuan (ORCID: https://orcid.org/0000-0001-9886-615X)
- W. J. Zheng (ORCID: https://orcid.org/0009-0002-1240-6393)
- Xinguo Hou (ORCID: https://orcid.org/0000-0003-2045-1290)
- Qincheng Qiao (ORCID: https://orcid.org/0009-0009-7900-2984)
- Wen Xue
- Chen Li (ORCID: https://orcid.org/0000-0002-0260-2182)
- Fuqiang Liu (ORCID: https://orcid.org/0000-0002-1593-9497)
- Jinzhe Li
Institutions
- Shandong University (CN)
- National University of Defense Technology (CN)
- Qilu Hospital of Shandong University (CN)
Publication Details
- Journal
- Digital Health
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1177/20552076251326223
- Citations
- 3
- Primary Topic
- Ocular Surface and Contact Lens
- Type
- article
- Field-Weighted Citation Impact
- 5.64
Funders
- National Key Research and Development Program of China