aceA framework for human evaluation of large language models in healthcare derived from literature review
With generative artificial intelligence (GenAI), particularly large language models (LLMs), continuing to make inroads in healthcare, assessing LLMs with human evaluations is essential to assuring safety and effectiveness. This study reviews existing literature on human evaluation methodologies for LLMs in healthcare across various medical specialties and addresses factors such as evaluation dimensions, sample types and sizes, selection, and recruitment of evaluators, frameworks and metrics, evaluation process,…
Human evaluation practices for LLMs in healthcare show gaps in reliability, generalizability, and applicability, undermining assurance of safety and effectiveness.
Evidence
- Peer-reviewedJournal of Systems and Software2026-07-17
- Peer-reviewedJournal of Clinical Medicine2025-09-01
- Peer-reviewedSoftware2025-11-13
- Peer-reviewedFrontiers in Artificial Intelligence2026-07-29
- Peer-reviewednpj Digital Medicine2024-09-28
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Truvace Impact Record TRV-2026-0355, v5: “A framework for human evaluation of large language models in healthcare derived from literature review.” Truvace, 2026-10-15. /record/TRV-2026-0355 (accessed at citation time). sha256 c1beb6de3618d36a…
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