MAKAR framework enhances patient-trial matching by combining domain-specific knowledge with structured AI reasoning to overcome the complexity of clinical trial eligibility criteria.

• Knowledge Augmentation Module enriches trial criteria with medical domain knowledge
• Reasoning Module applies multi-agent collaboration for more accurate patient eligibility assessment
• Domain-specific approach outperforms generic methods through targeted medical expertise
• Practical application addresses a critical bottleneck in clinical research recruitment

This innovation matters because efficient patient matching can accelerate clinical trials, reduce costs, and ultimately bring treatments to market faster. The multi-agent approach enables more nuanced understanding of complex medical criteria than traditional methods.

Enhancing Clinical Trial Patient Matching through Knowledge Augmentation and Reasoning with Multi-Agents