传统中医药中的大语言模型:一个广泛的综述
Yaxuan Ren1, Xufei Luo2,3,4,5, Ye Wang6
1School of Intelligent Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Journal of evidence-based medicine
|December 9, 2024
概括
大型语言模型 (LLM) 在传统中医 (TCM) 中显示出对知识管理和辅助诊断的希望. 然而,数据质量和TCM方面存在挑战.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能在医学中的应用
- 传统中医研究 传统中医研究
背景情况:
- 大型语言模型 (LLM) 在医学中越来越多地用于知识提取,管理和理解.
- 在中国传统医学 (TCM) 中LLM的应用仍未得到充分探索.
- 本研究概述了TCM中的LLM应用和挑战.
研究的目的:
- 综合审查传统中医药LLM申请的现状.
- 识别和分析与在TCM中实施LLMs相关的挑战.
- 评估LLM在TCM相关任务中的性能和准确性.
主要方法:
- 在五个数据库和谷歌学者 (2022年11月 - 2024年4月) 进行系统的文献搜索.
- 利用阿克西和奥马利的五阶段框架来确定研究.
- 从符合条件的研究中提取和组织数据,以描述LLM应用和TCM的表现.
主要成果:
- 确定了29项相关研究 (24篇同行评审文章,1篇评论,4篇预印稿).
- 核心应用包括TCM知识管理和辅助诊断/治疗.
- 在TCM实践者考试中,TCM专业的LLM获得了70%的准确率,超过了一般的LLM (60%).
结论:
- 法律学为TCM提供了巨大的潜力,特别是在知识提取和辅助诊断方面.
- 主要挑战包括数据质量,安全性,TCM数据复杂性和非定量诊断方法.
- 未来的方向包括跨学科合作,数据标准化和探索TCM的多模式AI.
相关概念视频
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