The paper presents a case-aware multimodal knowledge graph approach for medical image classification that retrieves similar cases, propagates knowledge via graph attention, and refines predictions with reliability estimates.
Pathreasoner-r1: Instilling structured reasoning into pathology vision-language model via knowledge-guided policy optimization.arXiv preprint arXiv:2601.21617, 2026
2 Pith papers cite this work. Polarity classification is still indexing.
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PathoSage is a three-stage framework using Structured Evidence Deliberation and a Beta-Bernoulli experience system to improve patch-level pathology reasoning by mitigating hallucinations and tool conflicts.
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Case-Aware Medical Image Classification with Multimodal Knowledge Graphs and Reliability-Guided Refinement
The paper presents a case-aware multimodal knowledge graph approach for medical image classification that retrieves similar cases, propagates knowledge via graph attention, and refines predictions with reliability estimates.
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PathoSage: Towards Multi-Source Evidence Adjudication in Pathology via Experience-Aware Agentic Workflow
PathoSage is a three-stage framework using Structured Evidence Deliberation and a Beta-Bernoulli experience system to improve patch-level pathology reasoning by mitigating hallucinations and tool conflicts.