Abstract: 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 forward.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.

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。