计算机工程与应用 ›› 2024, Vol. 60 ›› Issue (16): 1-18.DOI: 10.3778/j.issn.1002-8331.2312-0400

• 热点与综述 • 上一篇    下一篇

人工智能在中医诊疗领域的研究综述

苏尤丽,胡宣宇,马世杰,张雨宁,阿布都克力木·阿布力孜,哈里旦木·阿布都克里木   

  1. 新疆财经大学 信息管理学院,乌鲁木齐 830012
  • 出版日期:2024-08-15 发布日期:2024-08-15

Review of Research on Artificial Intelligence in Traditional Chinese Medicine Diagnosis and Treatment

SU Youli, HU Xuanyu, MA Shijie, ZHANG Yuning, Abudukelimu Abulizi, Halidanmu Abudukelimu   

  1. School of Information Management, Xinjiang University of Finance and Economics, Urumqi 830012, China
  • Online:2024-08-15 Published:2024-08-15

摘要: 中医诊疗领域正逐步迈向标准化、客观化、现代化与智能化。在此过程中,人工智能的融入极大地推动了中医诊疗、科学研究及中医传承的发展。从人工智能在中医领域的研究现状出发,梳理了从最初的专家系统和规则引擎,到逐渐成熟的传统机器学习算法,再到如今引领潮流的深度学习三个阶段,人工智能在中医领域的应用发展情况。总结了近年来涌现出的中医知识管理工具和大型模型,这些工具和模型为中医诊疗的智能化提供了坚实的支持。最后针对现阶段人工智能在中医领域中存在的数据公平性、多模态数据理解、模型鲁棒性、个性化医疗及可解释性等多重挑战进行分析。为应对这些挑战,需要持续探索并提出可能的解决方案,以推动中医诊疗智能化的深入发展,更好地满足人民健康需求。

关键词: 中医诊疗, 人工智能, 中医知识库, 中医大模型

Abstract: The field of traditional Chinese medicine (TCM) diagnosis and treatment is gradually moving towards standardization, objectification, modernization, and intelligence. In this process, the integration of artificial intelligence (AI) has greatly propelled the advancement of TCM diagnosis and treatment, scientific research, and TCM inheritance. The review starts from the current research status of AI in TCM, combs through the application and development of AI in TCM in three stages from expert system and rule engines, traditional machine learning algorithm to deep learning, and then summarizes the knowledge management tools and large language models of TCM in recent years. Finally, this paper analyzes the multiple challenges of data fairness, multimodal data understanding, model robustness, personalized medicine, and interpretability that exist at this stage of AI in TCM. To address these challenges, it is necessary to continuously explore and propose possible solutions to promote the in-depth development of intelligent TCM diagnosis and treatment, thus better meeting the health needs of people.

Key words: traditional Chinese medicine diagnosis and treatment, artificial intelligence, traditional Chinese medicine knowledge base, traditional Chinese medicine large language model