The Benefits of Using a Complete Probability Distribution when Decision Making: An Example in Anticoagulant Drug Therapy

Abstract

In this paper we aim to show how probabilistic prediction of a continuous variable could be more beneficial to a medical practitioner than classification or numeric/point prediction of the same variable in many scenarios. We introduce a probability density forecasting model that produces accurate estimates and achieves statistically consistent predicted distributions. An empirical evaluation of this approach on the problem of warfarin dosage prediction is described and a comparison of results obtained from our probabilistic models with a number of classification techniques on this problem is also shown.