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A pattern discovery visual analysis system for analyzing clinical data characteristics and generating patient cohorts
A pattern discovery visual analysis system for analyzing clinical data characteristics and generating patient cohorts
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机译：模式发现视觉分析系统，用于分析临床数据特征并生成患者队列
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摘要
In the pattern discovery visual analysis, a patient data table (14) is generated, which records attribute values for a set of attributes for each patient. For each patient, a positive or negative prediction for the target value of the target attribute is generated using the attribute value prediction pattern (20) for the w attributes (22). The prediction is positive if at least the threshold percentage (26) of the w attributes of the patient matches the prediction pattern, and negative otherwise. Patients are grouped into a confusion matrix (30) according to the positive or negative prediction and the actual value of the target attribute T in the patient data table. A display component (4) displays a representation (42) of patient statistics for the selected segment of the confusion matrix for each attribute of the w attributes. The representation is used to identify a patient cohort (44).
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