基于机器学习的非裔美国患者华法林最佳剂量预测

2013 IEEE International Conference on Automation Science and Engineering (CASE) Pub Date : 2013-11-07 DOI:10.1109/CoASE.2013.6653999

Ashkan Sharabiani, H. Darabi, A. Bress, L. Cavallari, E. Nutescu, K. Drozda

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引用次数: 15

摘要

本文提出了一种预测非裔美国患者华法林最佳剂量的新模型。采用多变量回归方法建立预测模型。剂量预测的准确性直接关系到患者的生命安全。我们表明，与所有其他可用的华法林最佳剂量预测方法相比，所提出的模型具有更好的准确性。

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Machine learning based prediction of warfarin optimal dosing for African American patients

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.

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

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