arXiv (All)
open access
PathCowork: Learning from real-world pathology practice to build AI copilots
Medical AI learns from the answers doctors record, but rarely from how they interpret the evidence to reach them. Here we introduce PathCowork, a framework that turns pathologists' narrated examinations into supervision for visual grounding and procedures that guide diagnostic AI agents. Synchronize
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Alignment Between Cardiologists and AI-Driven Diagnostic Systems: Mixed Methods Study.#214044
- Construction of AI Model for Precision Imaging Diagnosis of Cranial Diseases#1184344
- Human-AI Collaborative Intelligence for Improving Fetal Flow Management#1295266
- Pathology informatics fellowship training: Focus on molecular pathology#423217
- An Algorithm at the Table at Multidisciplinary Diagnostic Meetings: A Dramaturgical Analysis.#308776
Record · ID 1490836
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive