Can AI agents improve clinical trial matching?
Enhancing Clinical Trial Patient Matching through Knowledge Augmentation with Multi-Agents
November 25, 2024
https://arxiv.org/pdf/2411.14637This paper introduces MAKA, a multi-agent framework designed to improve patient matching for clinical trials using LLMs. MAKA uses multiple agents to augment trial criteria with external knowledge, addressing gaps in both the criteria and LLM understanding. Key points relevant to LLM-based multi-agent systems include: the use of specialized agents for knowledge probing, navigation, augmentation, and supervision; the dynamic integration of domain-specific knowledge to enhance LLM understanding; and the demonstration of improved performance in a patient-matching task compared to baseline LLM approaches.