Artificial intelligence-assisted glaucoma detection on color fundus images: with comorbidity and cross-institutional analysis
The proposed AI system can detect glaucoma on standard color fundus photographs with high accuracy across clinical environments and in the presence of comorbid eye diseases. The system may be a practical and affordable tool for large-scale glaucoma screening, particularly in institutions with limited resources.
Authors
- Yu‐Chieh Ko (ORCID: https://orcid.org/0000-0002-0818-4962)
- Henry Horng-Shing Lu
- Yen-Cheng Chen
- Wei-Shiang Chen
Institutions
- National Yang Ming Chiao Tung University (TW)
- Kaohsiung Medical University (TW)
- Cornell University (US)
- Kaohsiung Medical University Chung-Ho Memorial Hospital (TW)
- Taipei Veterans General Hospital (TW)
- En Chu Kong Hospital (TW)
Publication Details
- Journal
- Journal of the Chinese Medical Association
- Published
- 2025-09-04
- DOI
- https://doi.org/10.1097/jcma.0000000000001289
- Citations
- 1
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 1.36