Ong Chin Siang, Obey Nicholas T, Zheng Yanan, Cohan Arman, Schneider Eric B
Department of Surgery, Yale School of Medicine, New Haven, CT, USA.
Harvard T.H. Chan School of Public Health, Boston, MA, USA.
NPJ Digit Med. 2024 Dec 18;7(1):364. doi: 10.1038/s41746-024-01391-3.
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.
外科大语言模型(SurgeryLLM)是一个使用检索增强生成的大语言模型框架,当提供患者特定数据时,它能显著整合来自当前循证外科指南的特定领域知识。成功整合基于指南的信息是朝着提高外科医生效率、改善患者安全和优化手术结果迈出的重要一步。