Clinical Large Language Model Evaluation by Expert Review (CLEVER): Framework Development and Validation
The models show comparable performance on open-ended medical question answering, suggesting that health care-specific LLMs can outperform much larger general purpose LLMs in tasks that require understanding of clinical context. We test the validity of CLEVER evaluations by conducting interannotator agreement, interclass correlation, and washout period analysis.
Authors
- David Talby (ORCID: https://orcid.org/0000-0003-2782-5478)
- Veysel Kocaman (ORCID: https://orcid.org/0000-0002-0065-6478)
- Andrei Marian Feier (ORCID: https://orcid.org/0000-0002-1004-8839)
- Mustafa Aytuğ Kaya (ORCID: https://orcid.org/0009-0009-7824-6389)
Institutions
- George Mason University (US)
- John Snow (United States) (US)
Publication Details
- Journal
- JMIR AI
- Published
- 2025-11-02
- DOI
- https://doi.org/10.2196/72153
- Citations
- 2
- Primary Topic
- Topic Modeling
- Type
- article
- Field-Weighted Citation Impact
- 4.96