摘要
心电图是诊断心血管疾病的重要依据,论文提出了基于粗糙集的多变量决策树在分类诊断中的应用,并以窦性心率失常为例创建了多变量决策树,得到相应的分类规则。使用实际数据进行测试的结果表明,可以有效、快速地进行心率失常病例判别。
The ECG is the important basis of diagnosing the cardiovascular disease,this text has put forward the rough sets based approach for multivariate decision tree applied in ECG classification diagnostic.Using the sinus arrhythmia as an example to establish multivariate decision tree and get the corresponding classified rule.Using the real data to test indicates this method can effectively and fleetly differentiate the normal case from the arrhythmia.
出处
《计算机工程与应用》
CSCD
北大核心
2006年第13期206-208,共3页
Computer Engineering and Applications
基金
广东省科技攻关资助项目(编号:A10202001)
广州市科技攻关资助项目(编号:2004Z2-D0091)
关键词
粗糙集
多变量决策树
心电图
分类
rough sets,multivariate decision tree,ECG,classification
