AI RESEARCH
MedOpenClaw: Auditable Medical Imaging Agents Reasoning over Uncurated Full Studies
arXiv CS.CV
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ArXi:2603.24649v1 Announce Type: new Currently, evaluating vision-language models (VLMs) in medical imaging tasks oversimplifies clinical reality by relying on pre-selected 2D images that demand significant manual labor to curate. This setup misses the core challenge of realworld diagnostics: a true clinical agent must actively navigate full 3D volumes across multiple sequences or modalities to gather evidence and ultimately a final decision.