Machine learning based prediction of warfarin optimal dosing for African American patients
- Resource Type
- Conference
- Authors
- Sharabiani, Ashkan; Darabi, Houshang; Bress, Adam; Cavallari, Larisa; Nutescu, Edith; Drozda, Katarzyna
- Source
- 2013 IEEE International Conference on Automation Science and Engineering (CASE) Automation Science and Engineering (CASE), 2013 IEEE International Conference on. :623-628 Aug, 2013
- Subject
- Robotics and Control Systems
Mathematical model
Support vector machines
Equations
Artificial neural networks
Predictive models
Data models
Hemorrhaging
Warfarin dosing
machine learning
multivariable regression
support vector machines
neural networks
- Language
- ISSN
- 2161-8070
2161-8089
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.