通过人工智能和多式联络数据集成,推进中国传统医学的现代化
Pengfei Guo1,2, Mengmeng Jiang1,2, Shengquan Hu1,2
1The First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China.
Chinese medicine
|January 26, 2026
概括
人工智能 (AI) 解决了传统中医 (TCM) 数据中的挑战,增强了分析和研究. 人工智能在TCM中的应用,包括机器学习和大型语言模型,推动现代化和精密医学.
科学领域:
- 综合医学是一个整体医学.
- 计算生物学 计算生物学
- 医疗保健中的人工智能
背景情况:
- 传统中医 (TCM) 提供了独特的治疗优势,但面临着标准化和整合等数据挑战.
- 巨大的历史数据和人类在TCM的经验需要先进的方法,以有效地利用.
研究的目的:
- 审查人工智能 (AI) 在中国传统医学 (TCM) 应用的进展情况.
- 探索AI在克服数据限制和推进TCM研究和临床实践方面的作用.
主要方法:
- 审查人工智能技术,包括机器学习 (ML),深度学习 (DL),知识图 (KG) 和自然语言处理 (NLP).
- 分析跨多尺度TCM数据,研发,诊断和治疗以及大型语言模型 (LLM) 的AI应用.
主要成果:
- 人工智能显著提高了分析多模式TCM数据的效率和有效性.
- 人工智能有助于精确的数据分析,增强临床决策,并有助于目标发现和天然产品查.
- 在推进TCM研究和应用方面,LLM特别有前途.
结论:
- 人工智能技术对于TCM的现代化至关重要,它能够更深入地了解复杂的系统.
- 人工智能应用促进了数据驱动的TCM研究,基础科学和精密医学方面的创新.
- 人工智能的整合为TCM的未来带来了重大机遇.
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