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Information granules in medical differential diagnosis

机译:信息颗粒在医学鉴别诊断中的应用

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This paper discusses a correspondence between the core ideas of rough sets and medical differential diagnosis. Classically, a disease is defined as a set of symptoms, each of which gives the degree of confidence and coverage for the diagnosis. Diagnostic procedure mainly consists of the following three procedures: First, focusing mechanism (characterization) selects the candidates of differential diagnosis by using a set of symptoms. Secondly, additional set of symptoms make a differential diagnosis among the selected candidates. Finally, complications of other disease will be considered by symptoms which cannot be explained by the final candidates. This chapter mainly focuses on the first and second process and shows that thiese processes correponds to rules extracted by upper and lower approximation of supporting set of a given disease.
机译:本文讨论了粗糙集的核心思想与医学鉴别诊断之间的对应关系。通常,将疾病定义为一组症状,每种症状都会给出诊断的置信度和覆盖范围。诊断过程主要包括以下三个过程:首先,聚焦机制(特征化)通过使用一组症状来选择差异诊断的候选对象。其次,其他症状集合在所选择的候选者之间做出鉴别诊断。最后,其他疾病的并发症将由最终候选者无法解释的症状来考虑。本章主要关注第一个和第二个过程,并表明该过程与通过给定疾病的支持集的上下近似提取的规则相对应。

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