Enhancing diabetic retinopathy query responses: assessing large language model in ophthalmology
LLMs have the potential to provide accurate and comprehensive responses to DR-related questions, making them advantageous for ophthalmology applications. However, before clinical integration, further refinement is needed to address readability, and continuous validation assessments are imperative to ensure reliability.
Authors
- Yufeng Xu (ORCID: https://orcid.org/0000-0002-3672-1227)
- Kai Jin (ORCID: https://orcid.org/0000-0003-4369-2417)
- Xiangji Pan
- Zichang Su (ORCID: https://orcid.org/0009-0004-2917-7317)
- Yao Wang (ORCID: https://orcid.org/0000-0002-7149-4234)
- Juan Ye (ORCID: https://orcid.org/0000-0002-1948-2500)
- An Shao (ORCID: https://orcid.org/0000-0002-1795-4877)
- Hongkang Wu
Institutions
- Second Affiliated Hospital of Zhejiang University (CN)
Publication Details
- Journal
- British Journal of Ophthalmology
- Published
- 2025-06-30
- DOI
- https://doi.org/10.1136/bjo-2024-325861
- Citations
- 5
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 3.27
Funders
- National Natural Science Foundation of China