MedGuards introduces a multi-agent in-context learning framework for medical error detection and correction plus the KPCS metric, reporting improvements on four multilingual clinical note datasets.
A multimodal multi-agent framework for radiology report generation.arXiv preprint arXiv:2505.09787, 2025
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MARL-Rad trains region-specific and global agents with reinforcement learning on clinical rewards to produce more accurate radiology reports than prior methods on MIMIC-CXR and IU X-ray datasets.
MARCH is a multi-agent system mimicking radiology department hierarchy that generates more clinically accurate and linguistically correct CT reports than prior single-model approaches.
citing papers explorer
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MedGuards: Multi-Agent System for Reliable Medical Error Detection and Correction
MedGuards introduces a multi-agent in-context learning framework for medical error detection and correction plus the KPCS metric, reporting improvements on four multilingual clinical note datasets.
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Multi-Modal Multi-Agent Reinforcement Learning for Radiology Report Generation
MARL-Rad trains region-specific and global agents with reinforcement learning on clinical rewards to produce more accurate radiology reports than prior methods on MIMIC-CXR and IU X-ray datasets.
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MARCH: Multi-Agent Radiology Clinical Hierarchy for CT Report Generation
MARCH is a multi-agent system mimicking radiology department hierarchy that generates more clinically accurate and linguistically correct CT reports than prior single-model approaches.