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Hierarchical modeling in medical abnormality detection

机译:医疗异常检测中的层次建模

摘要

Hierarchal modeling is used to distinguish one state or class from three or more classes. In a first stage, a normal or other class is distinguished from a diseased or other groups of classes. If the results of the first stage classification indicate diseased or data within the groups of different classes, a subsequent stage of classification is performed. In a subsequent stage of classification, the data is classified to distinguish one or more other classes from the remaining classes. Using two or more stages, medical information is classified by eliminating one or more possible classes in each stage to finally identify a particular class most appropriate or probable for the data.
机译:层次建模用于将一个状态或类别与三个或更多类别区分开。在第一阶段,将正常或其他类别与患病或其他类别的类别区分开。如果第一阶段分类的结果表明疾病或不同类别的组内的数据,则执行下一阶段分类。在分类的下一阶段,将数据分类以将一个或多个其他类别与其余类别区分开。使用两个或多个阶段,通过在每个阶段中消除一个或多个可能的类别来分类医疗信息,以最终确定最适合或可能适用于数据的特定类别。

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