Liu Meng-Ling, Zhang Xin-You, Ding Liang, Pan Shu-Mao, Wu Di-Yao, Li Xiu-Yun
College of Computer Science, Jiangxi University of Chinese Medicine Nanchang 330004, China.
School of Pharmacy, Jiangxi University of Chinese Medicine Nanchang 330004, China.
Zhongguo Zhong Yao Za Zhi. 2021 Oct;46(20):5233-5239. doi: 10.19540/j.cnki.cjcmm.20210303.501.
Data mining is an important method to obtain the key information from a large amount of data, and it is widely applied in the research on the modernization of traditional Chinese medicine(TCM). The compatibility law of herbs is a key issue in the research of TCM prescriptions. This reflects the flexibility and effectiveness of TCM prescriptions, and it is also a crucial link to the development of TCM modernization. Therefore, it is the core purpose of the research on TCM prescriptions to find the compatibility law of herbs and clarify the scientific connotation. Data mining, as an effective method and an important approach, has formed a standardized system in the research of compatibility law of herbs, which can reveal the relationship between different Chinese herbs and summarize the internal rules in compatibility. Two hundred and twenty two effective papers were sorted out and categorized in this article. The results showed that data mining was mainly applied in finding the core Chinese herb pairs, summarizing the utility and attributes of TCM prescriptions, revealing the relationship between prescriptions, Chinese herbs and syndromes, finding the optimal dose of Chinese herbs, and producing the new prescriptions. The problems of data mining in research of herbs compatibility rules were summarized, and its development and trend in current researches were discussed in this article to provide useful references for the in-depth study of data mining in the compatibility law of Chinese herbs.
数据挖掘是从大量数据中获取关键信息的重要方法，在中医药现代化研究中得到广泛应用。中药配伍规律是中医方剂研究的关键问题。这体现了中医方剂的灵活性和有效性，也是中医药现代化发展的关键环节。因此，探寻中药配伍规律、阐明其科学内涵是中医方剂研究的核心目的。数据挖掘作为一种有效的方法和重要途径，在中药配伍规律研究中已形成规范体系，能够揭示不同中药之间的关系，总结配伍中的内在规律。本文整理并分类了222篇有效论文。结果表明，数据挖掘主要应用于寻找核心药对、总结中医方剂的功效与属性、揭示方剂、中药与证候之间的关系、寻找中药的最佳剂量以及创制新方剂。本文总结了数据挖掘在中药配伍规律研究中存在的问题，并探讨了其在当前研究中的发展及趋势，为深入开展中药配伍规律的数据挖掘研究提供有益参考。
