数据挖掘在中医药研究中的应用分析  

Application of data mining in the research of traditional Chinese medicine

作　　者：董雪燕[1] 祁烁[1] 姜苗[1] 韩丹阳[1] 董石[1] 崔玉[1] 

机构地区：[1]北京中医药大学东直门医院血液肿瘤科,硕士研究生100700

出　　处：《环球中医药》2017年第3期364-368,共5页Global Traditional Chinese Medicine

基　　金：2016年北京中医药大学优秀青年骨干教师专项计划(2016-JYB-QNJSZX019)

摘　　要：数据挖掘是从大量的、不完整的、复杂繁琐的数据中发现隐藏的、有价值的知识的过程。利用数据挖掘技术从中医累积的数据中探索和发现其中蕴含的规律,有利于中医学的继承、探索与发展。本文通过检索、总结中医学研究中数据挖掘技术相关文献,发现此类技术主要应用于中药方剂配伍规律、症状分析、辨证规律分析三方面;数据挖掘技术主要包括频数统计、聚类分析、因子分析、对应分析、关联规则、分类模型、贝叶斯网络、异常点分析等。Data mining is a process of discovering hidden and valuable knowledge from a large number of incomplete and complicated data. Using data mining techniques to explore and discover the law in the cumulative data of TCM,which is conducive to the inheritance,exploration and development of traditional Chinese medicine. The article summarizes the literature of using data mining techniques for traditional Chinese medicine research,or found the technology is mainly used in the law of compatibility of Chinese medical research,symptoms,syndrome differentiation regularity analysis; Data mining technology mainly include the frequency statistics,cluster analysis,factor analysis and correspondence analysis,association rules,classification model,Bayesian networks,abnormal point analysis,etc.

关 键 词：中医 数据挖掘 配伍规律 

分 类 号：R2-03[医药卫生—中医学]