Implementing Large Language Models in Health Care: Clinician-Focused Review With Interactive Guideline.

ABSTRACT:

Background

Large language models (LLMs) can generate outputs understandable by humans, such as answers to medical questions and radiology reports. With the rapid development of LLMs, clinicians face a growing challenge in determining the most suitable algorithms to support their work.

Objective

We aimed to provide clinicians and other health care practitioners with systematic guidance in selecting an LLM that is relevant and appropriate to their needs and facilitate the integration process of LLMs in health care.

Methods

We conducted a literature search of full-text publications in English on clinical applications of LLMs published between January 1, 2022, and March 31, 2025, on PubMed, ScienceDirect, Scopus, and IEEE Xplore. We excluded papers from journals below a s

SUBMITTER: Li H 

PROVIDER: S-EPMC12299950 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature