MISSING DATA APPROACHES IN MEDICAL DECISION SUPPORT SYSTEMS

摘要

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.