AI Agents in Clinical Medicine: A Systematic Review.

ABSTRACT:

Background

AI agents built on large language models (LLMs) can plan tasks, use external tools, and coordinate with other agents. Unlike standard LLMs, agents can execute multi-step processes, access real-time clinical information, and integrate multiple data sources. There has been interest in using such agents for clinical and administrative tasks, however, there is limited knowledge on their performance and whether multi-agent systems function better than a single agent for healthcare tasks.

Purpose

To evaluate the performance of AI agents in healthcare, compare AI agent systems vs. standard LLMs and catalog the tools used for task completion.

Data sources

PubMed, Web of Science, and Scopus from October 1, 2022, through August 5, 2025.

Study selection

Peer-re

SUBMITTER: Gorenshtein A 

PROVIDER: S-EPMC12407621 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature