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    • 6. 发明申请
    • MISSING DATA APPROACHES IN MEDICAL DECISION SUPPORT SYSTEMS
    • 医疗决策支持系统丢失数据处理方法
    • WO2006088983A3
    • 2007-03-01
    • PCT/US2006005388
    • 2006-02-16
    • SIEMENS MEDICAL SOLUTIONSKRISHNAN SRIRAMRAO R BHARAT
    • KRISHNAN SRIRAMRAO R BHARAT
    • G06F19/00
    • G16H50/20G16H10/60
    • Missing data is addressed in a medical decision support system. The classifier applied to the patient record with missing data is obtained as a function of the available data. For example, one of a plurality of different classifiers is selected based on the features available in the patient record to be classified. The different classifiers are developed using different feature sets. The classifier developed using a feature set closest to or a sub-set of the features available in the patient record is selected for classifying the patient record. As another example, features in a training set corresponding to features available in the patient record are used to build a classifier. The classifier is applied to the patient record by inputting the available features of the patient record.
    • 缺失的数据在医疗决策支持系统中得到解决。 作为可用数据的函数获得应用于具有缺失数据的病人记录的分类器。 例如,基于要分类的患者记录中可用的特征来选择多个不同分类器之一。 不同的分类器是使用不同的特征集开发的。 选择使用最接近或者患者记录中可用特征的子集的特征集开发的分类器用于对患者记录进行分类。 作为另一示例,使用对应于患者记录中可用特征的训练集中的特征来建立分类器。 通过输入患者记录的可用特征将分类器应用于患者记录。