August 26, 2025Open Access

AI Agents in Clinical Medicine: A Systematic Review

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Systematic review evaluates ai agents versus standard llms in healthcare, suggesting multi-agent systems improve performance.

AI agents significantly improve clinical task performance compared to baseline large language models, showing median gains of 53 percentage points.
Twenty peer-reviewed studies were analyzed, confirming that multi-agent systems function optimally for complex healthcare tasks with up to five agents.
Data extraction and synthesis highlighted architectures and performance metrics across clinical applications, revealing notable effectiveness in medication dosing.
Limitations include heterogeneous outcomes preventing meta-analysis, indicating a need for real-world data in future multi-center trials.

Gorenshtein et al. (2025) studied this question.

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August 26, 2025Open Access

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Authors

Systematic review evaluates ai agents versus standard llms in healthcare, suggesting multi-agent systems improve performance.

AI agents significantly improve clinical task performance compared to baseline large language models, showing median gains of 53 percentage points.
Twenty peer-reviewed studies were analyzed, confirming that multi-agent systems function optimally for complex healthcare tasks with up to five agents.
Data extraction and synthesis highlighted architectures and performance metrics across clinical applications, revealing notable effectiveness in medication dosing.
Limitations include heterogeneous outcomes preventing meta-analysis, indicating a need for real-world data in future multi-center trials.

Gorenshtein et al. (2025) studied this question.

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