基于粗糙集的医疗数据挖掘研究与应用  

Research and application on medical data mining based on rough sets

作　　者：叶明全[1] 伍长荣[2] 胡学钢[3] 

机构地区：[1]皖南医学院计算机教研室,安徽芜湖241002 [2]安徽师范大学数学计算机学院,安徽芜湖241002 [3]合肥工业大学计算机与信息学院,合肥230009

出　　处：《计算机工程与应用》2010年第21期232-234,共3页Computer Engineering and Applications

基　　金：安徽省教育厅自然科学基金项目No.KJ2008B039~~

摘　　要：医疗数据挖掘能够对现有病历数据库中数据进行自动分析并且提供有价值的医学知识。针对临床病历数据库中存在大量重复样本和冗余属性,从而影响医疗诊断的精度和速度这一问题,建立了基于信息论的粗糙集理论模型和SQL语言之间的关系,提出了基于SQL语言的条件信息熵属性约简算法,利用数据库查询语言实现了数据清洗、求核和属性约简等过程。实验结果表明该算法实现简单,运行效率高,为粗糙集理论更广泛地应用于具体的医疗数据挖掘提供了一种方法。Medical data mining can generate effective knowledge rules from medical record database.It is found that the precision and speed of medical diagnosis are unsatisfied due to large-scale repeating data and redundant attributes in medical data during practical applications.To solve the problem,this paper establishes relation of rough set theory based on information view and SQL language,and conditional information entropy attributes reduction algorithm based on SQL language is put for-ward.Experiments show that the algorithm can be easily realized taking advantage of database query language and is more efficient.It establishes a method by which rough set theory is widely used in material medical data mining.

关 键 词：粗糙集 属性约简 条件信息熵 结构化查询语言(SQL) 医疗数据挖掘 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]