Evaluation of ophthalmic large language models: quantitative vs. qualitative methods
This review outlines the spectrum of quantitative and qualitative evaluation metrics adopted in existing studies, highlights key challenges in LLM evaluation, to catalyze further work towards standardized and domain-specific evaluation. Robust evaluation to effectively validate clinical LLM applications is crucial in closing the gap towards clinical integration.
Authors
- Arun James Thirunavukarasu (ORCID: https://orcid.org/0000-0001-8968-4768)
- Chrystie Wan Ning Quek
- Daniel Shu Wei Ting (ORCID: https://orcid.org/0000-0003-2264-7174)
- Ting Fang Tan
Institutions
- Singapore National Eye Center (SG)
- London School of Hygiene & Tropical Medicine (GB)
- Singapore Eye Research Institute (SG)
- Duke-NUS Medical School (SG)
- Smith-Kettlewell Eye Research Institute (US)
- Stanford University (US)
Publication Details
- Journal
- Current Opinion in Ophthalmology
- Published
- 2025-09-03
- DOI
- https://doi.org/10.1097/icu.0000000000001171
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00