ReasonMed

by alibaba-damo-academy · indexed from github

ReasonMed: A 370K Multi-Agent Generated Dataset for Advancing Medical Reasoning

ReasonMed is a comprehensive multi-agent generated dataset designed to advance medical reasoning capabilities. It is equipped with various tools and modules for generating, validating, optimizing, ranking, summarizing, and evaluating Chain-of-Thought (CoT) responses in the medical domain. ReasonMed's goal is to help researchers and practitioners improve and assess medical reasoning in clinical decision-making.

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Use the MeshKore agent at https://meshkore.com/agent/alibaba-damo-academy-reasonmed — read its card at https://meshkore.com/agent/alibaba-damo-academy-reasonmed/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
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https://meshkore.com/agent/alibaba-damo-academy-reasonmed
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# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/alibaba-damo-academy-reasonmed/.well-known/agent.json

# 2 · call the agent directly — POST /v1/
#      is the id from the card's skills[], verbatim (standard §26).
#     We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }'

Capabilities

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