数据挖掘中的分类算法及其在中医证候学中的应用  

Application of classification algorithms for data mining in TCM syndrome research

作　　者：陈克龙[1] 樊永平[1] 

机构地区：[1]首都医科大学附属北京天坛医院,北京100050

出　　处：《中华中医药杂志》2011年第3期469-473,共5页China Journal of Traditional Chinese Medicine and Pharmacy

基　　金：首都医学发展科研基金(No.2005-SF-Ⅰ)~~

摘　　要：中医研究领域中,辨证是中医学的核心,也是确保疗效的前提。为了研究中医辨证分类规律,数据挖掘近年来广泛用于其中,成为数据挖掘用于中医药领域研究的一个特点。分类算法是数据挖掘中的最重要的技术之一。文章简要介绍了分类算法中的常用技术如决策树分类、贝叶斯分类、神经网络分类等,同时对其在中医证候分类研究中的应用进行概括,希望能为未来中医证候学的研究提供一个方向。In the field of TCM research,differentiation is the core of it and the Precondition to ensure efficacy.In order to study the classification rule of TCM,data mining has been widely used on it in recently years,and data mining on Traditional Chinese medicine（TCM） syndrome has been a hot issue of that used in TCM.Classification is one of the most important techniques in data mining.This paper introduced the techniques such as decision trees,beyes,neural network,and discussed the application of these techniques in Traditional Chinese Medical Research of Syndrome in order to indicate a direction for the research of TCM Syndrome in future.

关 键 词：数据挖掘 分类算法 中医证候 

分 类 号：R241[医药卫生—中医诊断学]