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人工智能在中医药的研究现状及展望
引用本文:李心怡,罗思言,徐常胜,丁贵广,张勇东,田贵华. 人工智能在中医药的研究现状及展望[J]. 生物医学转化, 2022, 3(3): 69-73
作者姓名:李心怡  罗思言  徐常胜  丁贵广  张勇东  田贵华
作者单位:北京中医药大学东直门医院,北京 100700;中国科学院自动化研究所,北京 100864;清华大学软件学院,北京 100084;中国科学技术大学信息学院,安徽 合肥 230026
基金项目:国家中医药管理局青年岐黄学者支持项目(国中医药人教发〔2020〕7号)
摘    要:中医药在世界范围内难以被广泛接受的主要问题是缺少足够客观定量的数据支撑和完备而自洽的理论体系。此外,传统中医术语的模糊性、理论知识的难以理解性、治疗思维的抽象性、中医医案的繁杂性也对中医现代化发展带来了极大的挑战。随着信息技术的日新月异,大数据和人工智能技术为规范中医诊疗数据、构建智能中医诊疗体系以及突破传统中医诊疗模式提供了新方法,进一步推动了中医药智能化的发展。经过半个多世纪的发展,中医与人工智能技术的融合逐步深入,取得了一定的应用成果,如中医药中医信息化数据库、中医四诊采集设备、中医辅助诊疗系统以及智慧中医健康管理等。但就目前而言,中医药智能化发展中仍存在数据标准欠缺、相关制度不够完善、交叉人才匮乏等问题,未来还需进一步建立规范的数据标准,完善数据共享、知识产权、伦理规范等法律法规,加速培养学科交叉复合型人才,创新思维革新医疗模式等,促进人工智能背景下的中医药创新发展。本文从知识发现与机器学习的角度,对人工智能在中医药的研究进展概括总结,以期为中医药智能化提供助力。

关 键 词:人工智能;中医;机器学习;知识发现

Current status and future prospects of artificial intelligence in traditional Chinese medicine
Li Xinyi,Luo Siyan,Xu Changsheng,Ding Guiguang,Zhang Yongdong,Tian Guihua. Current status and future prospects of artificial intelligence in traditional Chinese medicine[J]. Biomedical Transformation, 2022, 3(3): 69-73
Authors:Li Xinyi  Luo Siyan  Xu Changsheng  Ding Guiguang  Zhang Yongdong  Tian Guihua
Affiliation:Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing 100700 , China;Institute of Automation of the Chinese Academy of Sciences, Beijing 100864 , China;School of Software, Tsinghua University, Beijing 100084 , China;School of Information, University of Science and Technology of China, Hefei 230026 , Anhui, China
Abstract:Traditional Chinese Medicine (TCM) has not been widely accepted in the world for the lack of objective data and complete theoretical system. In addition, the ambiguous of language, the difficulty in understanding theoretical knowledge, the abstractness of therapeutic mind, and the complexity of medical records have also brought great challenges to the development of TCM modernization. With the rapid development of information technology, big data and Artificial Intelligence (AI) technology have provided new methods for standardizing TCM diagnosis and treatment data, building an intelligent TCM diagnosis and treatment system and breaking through TCM diagnosis and treatment model, further promoting the development of TCM intellectualization. After more than half a century of development, the integration of TCM and AI technology has gradually deepened and certain application results have been achieved, such as the information database of TCM, four diagnosis collection equipment of TCM, the clinical auxiliary diagnosis and treatment system of TCM and intelligent health management of TCM, etc. However, for now, there are still some problems in the intellectualized development of TCM, such as the lack of data standards, the insufficient improvement of related systems and the lack of talents with interdisciplinary backgrounds, etc. The focus of future work is to establish normative data standards, improve relevant laws and regulations on data sharing, intellectual property rights, and cord of ethics, so as to promote the innovative development of TCM in the AI background. The study summarizes the progress of AI in TCM from the perspective of knowledge discovery and machine learning, in order to provide assistance for the intellectualization of TCM.
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