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Updated: Jan 8, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

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计算机辅助口语尸检:将大型语言模型与医生进行比较,以确定塞拉利昂2019-2022年6939例死亡的原因

Richard Wen1, Anteneh Tesfaye Assalif2,3, Andy Sze-Heng Lee2

  • 1Centre for Global Health Research, St. Michael's Hospital, Unity Health Toronto and University of Toronto, 30 Bond St, Toronto, Ontario, M5B 1W8, Canada. rwen@torontomu.ca.

BMC medicine
|December 24, 2025
PubMed
概括

与传统方法相比,GPT-5等大型语言模型 (LLM) 在从口头尸检 (VA) 确定死亡原因 (COD) 方面表现优异. 这项研究提供了将LLM与医生编码集成的证据,以提高VA数据质量.

关键词:
人工智能的人工智能是人工智能.死亡原因 死亡原因计算机辅助诊断是一种计算机辅助诊断.全球卫生健康 全球卫生健康机器学习 机器学习数学模型的数学模型.死亡率 死亡率 死亡率自然语言处理自然语言处理.医生 医生 医生监督 监督 监督 监督 监督 监督

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