A computer-based system to determine whether patients should be treated as inpatients or outpatients. The invention makes personalized predictions about the risk and timing of adverse outcomes for the patient, and further assesses how this risk and timing may vary if the patients are treated as inpatients or outpatients. This information informs how patients are assigned to an appropriate therapy. The invention includes logic relevant to predicting patient risk, decoupling patient risk into components inherent to the patient as well as additions/subtractions associated with the choice of treatment, and predicting the timing of adverse outcomes given censored data. The invention can be extended to use in a broad range of other application domains (e.g., matching learners to courses either offered in-classroom or online for education).
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