MedFlowBench evaluates VLM agents on full radiology and pathology studies by requiring both task answers and verifiable evidence like key slices and regions of interest, revealing that answer-only scores overestimate performance.
Cxr-agent: Vision-language models for chest x-ray interpretation with uncertainty aware radiology reporting,
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GAZE framework with viewer tools and literature retrieval achieves 58.2 mAP@0.3 lesion localization and 34.9% top-1 diagnostic accuracy on 906 rare brain MRI cases in zero-shot setting, with larger gains on rarest pathologies.
A survey that deconstructs LLM agent systems via a methodology-centered taxonomy linking design principles to emergent behaviors, applications, and challenges.
citing papers explorer
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MedOpenClaw and MedFlowBench: Auditing Medical Agents in Full-Study Workflows
MedFlowBench evaluates VLM agents on full radiology and pathology studies by requiring both task answers and verifiable evidence like key slices and regions of interest, revealing that answer-only scores overestimate performance.
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GAZE: Grounded Agentic Zero-shot Evaluation with Viewer-Level Tools and Literature Retrieval on Rare Brain MRI
GAZE framework with viewer tools and literature retrieval achieves 58.2 mAP@0.3 lesion localization and 34.9% top-1 diagnostic accuracy on 906 rare brain MRI cases in zero-shot setting, with larger gains on rarest pathologies.
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Large Language Model Agent: A Survey on Methodology, Applications and Challenges
A survey that deconstructs LLM agent systems via a methodology-centered taxonomy linking design principles to emergent behaviors, applications, and challenges.