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SurgeryLLM: a retrieval-augmented generation large language model framework for surgical decision support and workflow enhancement

  • Chin Siang Ong,
  • Nicholas T. Obey,
  • Yanan Zheng,
  • Arman Cohan,
  • Eric B. Schneider

摘要

SurgeryLLM, a large language model framework using Retrieval Augmented Generation demonstrably incorporated domain-specific knowledge from current evidence-based surgical guidelines when presented with patient-specific data. The successful incorporation of guideline-based information represents a substantial step toward enabling greater surgeon efficiency, improving patient safety, and optimizing surgical outcomes.