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Knowledge Discovery in Medical Multi-databases: A Rough Set Approach

机译:医疗多数据库中的知识发现:粗略的方法

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Since early 1980's, due to the rapid growth of hospital information systems (HIS), electronic patient records are stored as huge databases at many hospitals. One of the most important problems is that the rules induced from each hospital may be different from those induced from other hospitals, which are very difficult even for medical experts to interpret. In this paper, we introduce rough set based analysis in order to solve this problem. Rough set based analysis interprets the conflicts between rules from the viewpoint of supporting sets, which are closely related with dempster-shafer theory(evidence theory) and outputs interpretation of rules with evidential degree. The proposed method was evaluated on two medical databases, the experimental results of which show that several interesting relations between rules, including interpretation on difference and the solution of conflicts between induced rules, are discovered.
机译:自20世纪80年代初,由于医院信息系统(他)的快速增长,电子患者记录在许多医院存储为庞大的数据库。最重要的问题之一是,每个医院所诱导的规则可能与其他医院引起的规则不同,即使医学专家解释也是非常困难的。在本文中,我们引入了基于粗糙的分析,以解决这个问题。基于粗糙集的分析解释了从支持集的角度来解释规则之间的冲突,这与Dempster-Shafer理论(证据理论)密切相关,并输出了证据学位的解释。在两个医学数据库中评估了所提出的方法,实验结果表明,规则之间的几个有趣的关系,包括涉及规则之间的差异和冲突解决的解释。

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