基于Rough Sets的中医指症挖掘研究与应用  

Research and application on TCM diagnosis mining base on Rough Sets.

作　　者：丁卫平[1] 管致锦[1] 顾春华[2] 

机构地区：[1]南通大学计算机科学与技术学院,江苏南通226019 [2]南通市中医院,江苏南通226006

出　　处：《计算机工程与应用》2008年第7期234-237,共4页Computer Engineering and Applications

基　　金：江苏省高校自然科学基础研究项目(No.02KJB520004,No.05KJB520107) ;南通大学自然科学基金项目(No.05Z061);南通大学通信与信息系统学科科技创新资助

摘　　要：针对中医病历数据库中指症样本维数较大、数据特征和属性冗余量较多等特征,在对Rough Sets基本理论和属性约简算法研究的基础上,提出了将属性频度和属性重要性相结合的GENRED_GROWTH中医指症挖掘算法,并进行了基于GENRED_GROWTH的中医指症挖掘原型系统设计与实现。通过分析和实验结果表明:该算法能较好地进行中医指症属性约简,分类精度较高,并且能抽取中医指症相关诊断规则以辅助医生的诊断和治疗。According to the problems existing which include the much larger numbers of dimensions of the sample,much heavier data features and redundant attribution of TCM （Traditional Chinese Medicine） diagnosis,the paper provid the GENRED_GROWTH TCM diagnosis algorithm combining the frequency with the importance of attribution on the basic of research and study of the basic theory and attribution reduction of Rough Sets.Meanwhile the algorithm is applied in the prototype data mining experiment on TCM diagnosis.The resuhs show that the algorithm can be used to reduce redundant attributes in data mining on TCM diagnosis,and the classification accuracy is higher.And it performs accurately on TCM diagnosis datasets.The useful information for the diagnosis can be extracted in order to help to provide some decision-making for the assistant diagnoses.

关 键 词：ROUGH SETS 属性约简 中医指症 数据挖掘 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]