Name
Title | ||
|---|---|---|
Machine learning based prediction of warfarin optimal dosing for African American patients |
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. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/CoASE.2013.6653999 | Automation Science and Engineering |
Keywords | Field | DocType |
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,Warfarin dosing,machine learning,multivariable regression,neural networks,support vector machines | Multivariable calculus,Regression,Regression analysis,Computer science,Support vector machine,Artificial intelligence,African american,Artificial neural network,Warfarin,Dosing,Machine learning | Conference |
ISSN | Citations | PageRank |
2161-8070 | 2 | 0.46 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sharabiani, A. | 1 | 8 | 0.96 |
| Darabi, H. | 2 | 16 | 2.61 |
| Adam Bress | 3 | 4 | 1.96 |
| Larisa Cavallari | 4 | 2 | 0.79 |