#medical-diagnosis3 articles

3 articles

AIBullisharXiv – CS AI · 6h ago2

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CARE: Towards Clinical Accountability in Multi-Modal Medical Reasoning with an Evidence-Grounded Agentic Framework

Researchers introduce CARE, an evidence-grounded agentic framework for medical AI that improves clinical accountability by decomposing tasks into specialized modules rather than using black-box models. The system achieves 10.9% better accuracy than state-of-the-art models by incorporating explicit visual evidence and coordinated reasoning that mimics clinical workflows.

AIBullisharXiv – CS AI · 6h ago2

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MedCollab: Causal-Driven Multi-Agent Collaboration for Full-Cycle Clinical Diagnosis via IBIS-Structured Argumentation

Researchers have developed MedCollab, a multi-agent AI framework that uses structured argumentation and causal reasoning to improve clinical diagnosis accuracy. The system outperforms traditional LLMs by reducing medical hallucinations and providing more transparent, clinically compliant diagnostic processes through hierarchical consultation workflows.

AIBullisharXiv – CS AI · 6h ago2

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Linking Knowledge to Care: Knowledge Graph-Augmented Medical Follow-Up Question Generation

Researchers developed KG-Followup, a knowledge graph-augmented large language model system that generates medical follow-up questions for pre-diagnostic assessment. The system combines structured medical domain knowledge with LLMs to improve clinical diagnosis efficiency, outperforming existing methods by 5-8% in recall benchmarks.