Predicting warfarin dosage from clinical data: A supervised learning approach

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ObjectiveSafety of anticoagulant administration has been a primary concern of the Joint Commission on Accreditation of Healthcare Organizations. Among all anticoagulants, warfarin has long been listed among the top ten drugs causing adverse drug events. Due to narrow therapeutic range and significant side effects, warfarin dosage determination becomes a challenging task in clinical practice. For superior clinical decision making, this study attempts to build a warfarin dosage prediction model utilizing a number of supervised learning techniques.

论文关键词:Classifier ensemble,Support vector regression,Multilayer perceptron,Model tree,Dosage prediction,Warfarin

论文评审过程:Received 20 October 2011, Revised 2 April 2012, Accepted 2 April 2012, Available online 24 April 2012.

论文官网地址:https://doi.org/10.1016/j.artmed.2012.04.001