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Abstract: Medical image analysis increasingly relies on large vision-language models (VLMs), yet most systems remain single-pass black boxes that offer limited control over reasoning, safety, and spatial grounding. We propose R^4, an agentic framework that decomposes medical imaging workflows…
The main features of faiyazabdullah/multimodalmedagent are: Clinical Reasoning Agents, Radiology and Imaging Agents.
Projects with overlapping indexed features include: actava-ai/chi-bench — C linical H ealthcare I n-Situ Environment Benchmark for long-horizon, policy-rich healthcare workflow agents. bowang-lab/medrax — MedRAX: Medical Reasoning Agent for Chest X-ray - ICML 2025. freedomintelligence/openclaw-medical-skills — The largest open-source medical AI skill library for OpenClaw. imyangc7/lungnoduleagent — Classifies lung adenocarcinoma nodules into AIS / MIA / IAC through a four-stage pipeline — nodule detection, sizing,… luczot/veritas — Verifiable Epistemic Reasoning for Image-Derived Hypothesis Testing via Agentic Systems. truhnlab/contrastive-agent-reasoning — by Zihao Zhao, Frederik Hauke, Juliana De Castilhos, Sven Nebelung, and Daniel Truhn.
MedRAX: Medical Reasoning Agent for Chest X-ray - ICML 2025
The largest open-source medical AI skill library for OpenClaw.
Classifies lung adenocarcinoma nodules into AIS / MIA / IAC through a four-stage pipeline — nodule detection, sizing, report generation, and multi-agent clinical debate — that mirrors how a real radiology team works.
C linical H ealthcare I n-Situ Environment Benchmark for long-horizon, policy-rich healthcare workflow agents