基于文献的中医证候规范方法研究

目的:从文献中挖掘中医证候信息,进行规范研究,以期对中医的规范化,现代化起到一点借鉴作用.方法:选取了西医病名的4个疾病,在中国生物医学文献数据库中进行检索血瘀证的症状数据,其中包括血瘀证及其兼证的症状信息,从“证候-疾病(证-病)”的角度进行了聚类分析和判别分析.另外,选取糖尿病作为基本疾病来研究其证候规律,即“疾病-证候(病-证)”的角度来进行分析.将所有病种所有症状信息进行提取,建立数据库,将症状、证候的词语进行规范,使其成为最小中医信息单元,输入计算机,转换成计算机可以识别计算的数据.使用WEKA进行判别分析.SPSS进行聚类分析,得出证候信息.结果:通过以上方法进行统计分析后,得出的证候信息跟现有的证候标准相似.说明文献作者对现有标准是比较认可的.或多或少都受到了现有标准的影响.但是这个结果不能完全被现有标准所包括,考虑是因为临床疾病的多样性,复杂性造成的,所以现有标准有待进一步完善.结论:通过对文献进行数据挖掘,用统计分析软件对数据进行分析,总结出几种疾病的证候特点的证候研究方法是可行的,同时提出了证候规范化方法研究需要引入证素的概念.

Research on TCM Syndrome Standardization Based on Literature

Objective: To explore a method of syndrome standardization based on syndrome information from literature,in order to provide reference for the normalization and modernization for the TCM.Methods: Four diseases were applied from western medicine and checked in the China Biology and Medical disc(CBM disc).And articles,which refer the information of blood stasis syndromes as well as accompanying symptoms,were downloaded.Cluster analysis and discriminant analysis were carried out in terms of "syndrome-disease".And diabetes is the basic disease to study the regular of the syndrome,namely in terms of "syndrome-disease".Make a database of these TCM syndromes and normalize the data.The symptoms were transformed into the so-called smallest units of TCM and put into computers.The WEKA for discriminant analysis and SPSS for cluster analysis were applied to get syndrome information.Results: The Syndromes we got are similar to the existing standards.The existing standards are approved to some extent by the authors of the articles.There are more or less impacts from existing standards.However,because of the diversity and the complexity of clinical diseases,the results of the trial cannot be covered by the existing standards completely.So the existing standards need further improvement.Conclusion: It is feasible to summarize the characteristic and regular of the syndromes from literature by data analysis.At the same time,Zhengsu(Syndrome Factors) is necessary put forward to the standardization of syndromes.