bowang-lab/MedRAX

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1218 stars · 204 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

MedRAX is a medical reasoning agent framework that integrates chest X-ray analysis tools (segmentation, grounding, report generation, disease classification) with multimodal LLMs like GPT-4o into a unified orchestration layer built on LangChain and LangGraph. It ships with ChestAgentBench, a 2,500-query benchmark, and a Gradio-based interface for interactive CXR interpretation.

Use cases

• interpret chest x-rays with an ai agent
• generate radiology reports from cxr images
• segment anatomical structures in chest x-rays
• classify lung pathologies in x-ray images
• benchmark medical ai agents on complex queries
• orchestrate medical imaging models with an llm
• localize findings in chest x-rays

When to choose

• you need a unified agent to orchestrate multiple chest X-ray analysis models without training
• you want a research baseline or benchmark for medical agentic AI on CXR tasks
• you need DICOM processing plus segmentation, grounding, and reporting in one pipeline

When to avoid

• you need a clinically certified diagnostic product for patient care
• your use case involves imaging modalities other than chest X-rays
• you want a lightweight model without GPT-4o API dependency or GPU-heavy submodels

Facets

framework · maturity active

agent-framework machine-learning image-processing llm-inference rag healthcare artificial-intelligence computer-vision python self-hosted cross-platform chest-xray medical-imaging langchain langgraph multimodal chestagentbench report-generation segmentation gradio research ai-agents docker

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markdown · JSON · MCP: product_card(name="bowang-lab/MedRAX")