Title :
Machine learning based prediction of warfarin optimal dosing for African American patients
Author :
Sharabiani, Anooshiravan ; Darabi, Hooman ; Bress, Adam ; Cavallari, Larisa ; Nutescu, Edith ; Drozda, Katarzyna
Abstract :
This paper proposes a new model for predicting the optimal warfarin dosing for African American patients. The prediction model is created using the multivariable regression method. The accuracy of dosing prediction is directly related to patient´s safety. We show that the proposed model has better accuracy compare to all other available prediction methods for optimal dosing of warfarin.
Keywords :
learning (artificial intelligence); medical computing; patient treatment; regression analysis; African American patients; machine learning based prediction; multivariable regression method; patient safety; warfarin optimal dosing prediction; Artificial neural networks; Data models; Equations; Hemorrhaging; Mathematical model; Predictive models; Support vector machines; Warfarin dosing; machine learning; multivariable regression; neural networks; support vector machines;
Conference_Titel :
Automation Science and Engineering (CASE), 2013 IEEE International Conference on
Conference_Location :
Madison, WI
DOI :
10.1109/CoASE.2013.6653999