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

fYear

2013

fDate

17-20 Aug. 2013

Firstpage

623

Lastpage

628

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Automation Science and Engineering (CASE), 2013 IEEE International Conference on

Conference_Location

Madison, WI

ISSN

2161-8070

Type

conf

DOI

10.1109/CoASE.2013.6653999

Filename

6653999

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2062396