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Knowledge discovery in medical multi-databases:a rough set approach

机译:医学多数据库中的知识发现:粗糙集方法

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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1980年代初以来,由于医院信息系统(HIS)的迅速发展,电子病历被作为大型数据库存储在许多医院中。最重要的问题之一是,各医院产生的规则可能与各医院产生的规则不同。为了解决这个问题,本文介绍了基于粗糙集的分析方法。基于粗糙集的分析方法从支持集的角度解释了规则之间的冲突,这是非常紧密的。该方法与Dempster-Shafer理论(证据理论)相关,并以证据的程度输出规则的解释。该方法在两个医学数据库中进行了评估,实验结果表明,规则之间存在一些有趣的关系,包括对差异的解释和对结果的求解。发现了诱导规则之间的冲突。

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