Enhancing diabetic retinopathy diagnosis and grading: a retrospective study on AI-assisted decision making and cost analysis
AI assistance shows potential in improving the accuracy of DR diagnosis and grading. Despite the associated costs, AI enables ophthalmologists to achieve superior diagnosis, facilitating earlier DR detection and treatment.
Authors
- Xiaojun Xu (ORCID: https://orcid.org/0000-0001-5030-7201)
- Yan Liu (ORCID: https://orcid.org/0000-0003-4242-228X)
- Yan Li (ORCID: https://orcid.org/0000-0003-4962-9910)
- Xinyi Liu (ORCID: https://orcid.org/0000-0001-5333-8054)
- Lili Feng (ORCID: https://orcid.org/0000-0002-6760-3813)
- Jiaying Zhang (ORCID: https://orcid.org/0009-0000-6855-7823)
- Yun Su (ORCID: https://orcid.org/0000-0001-7981-1874)
- Xianqun Fan
- Xuefei Song (ORCID: https://orcid.org/0000-0002-5666-6894)
- Linna Lu
Institutions
- Shanghai Jiao Tong University (CN)
- Shanghai Ninth People's Hospital (CN)
- Shanghai Institute of Hematology (CN)
Publication Details
- Journal
- British Journal of Ophthalmology
- Published
- 2025-10-20
- DOI
- https://doi.org/10.1136/bjo-2025-327442
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00