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心脏超声诊断数据挖掘尝试——粗糙集理论运用
Data mining of echocardiograghy based on rough set theory
【摘要】 本文的目的是要寻找心脏超声实测指标与心脏病变类型的关系,以建立模型,协助临床医生更科学更准确地进行诊断。但超声实测数据函数关系复杂,难以用传统的统计方法进行分析。因此本文采用粗糙集理论挖掘心脏超声实测指标与心脏病变类型的规则。结果把挖掘出的规则应用到心脏超声诊断上,取得了令人满意的效果。
【Abstract】 The purpose of this paper is to find the relations between the index of the echocardiography and the type of the cardiopathy. It can help the clinician diagnose more scientifically and more accurately. But the mathematical function relationship of the data is complex. It is difficult to analyze with the traditional statistics means. Therefore, the paper use the rough set theory to achieve the purpose. The result which is used on the echocardiography acquires satisfied effect.
【关键词】 粗糙集理论;
Rosetta软件;
数据挖掘;
心脏超声;
【Key words】 roughset theory; rosetta sortware; mining data; echocardiograghy;
【Key words】 roughset theory; rosetta sortware; mining data; echocardiograghy;
- 【文献出处】 医学信息 ,Medical Information , 编辑部邮箱 ,2005年01期
- 【分类号】R311
- 【被引频次】7
- 【下载频次】186