reviewJAMAOct 15, 2024GREEN OA

Testing and Evaluation of Health Care Applications of Large Language Models

Stanford Medicine · Stanford University · +4 more institutions

PubMed
Indexed incrossrefpubmed

Abstract

Importance

Large language models (LLMs) can assist in various health care activities, but current evaluation approaches may not adequately identify the most useful application areas.

Objective

To summarize existing evaluations of LLMs in health care in terms of 5 components: (1) evaluation data type, (2) health care task, (3) natural language processing (NLP) and natural language understanding (NLU) tasks, (4) dimension of evaluation, and (5) medical specialty. Data Sources: A systematic search of PubMed and Web of Science was performed for studies published between January 1, 2022, and February 19, 2024. Study Selection: Studies evaluating 1 or more LLMs in health care. Data Extraction and Synthesis: Three independent reviewers categorized studies via keyword searches based on the data used, the health care tasks, the NLP and NLU tasks, the dimensions of evaluation, and the medical specialty.

Citation impact

402
total citations
FWCI
42.79
Percentile
100%
References
71
Citations per year

Authors

19

Topics & keywords

Keywords
  • Medicine
  • Health care
  • Intensive care medicine
UN Sustainable Development Goals
  • Quality Education
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