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A comprehensive scheme of patient similarity based on different types of patient features and the corresponding similarity measurements was proposed. Patient similarity was used in building a predictive model where training samples similar to the index patient were selected instead of randomly selected samples. The predictive models using the proposed patient similarity measurement outperformed those using Euclidean distance based similarity and those not using patient similarity.
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