A Bayesian Estimation Framework for Pharmacogenomics Driven Warfarin Dosing: A Comparative Study

Date

2015-09-01

Author

Oztaner, Serdar Murat
Taşkaya Temizel, Tuğba
Erdem, S. Remzi
ÖZER, Mahmut

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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The incorporation of pharmacogenomics information into the drug dosing estimation formulations has been shown to increase the accuracy in drug dosing and decrease the frequency of adverse drug effects in many studies in the literature. In this paper, an estimation framework based on the Bayesian structural equation modeling, which is driven by pharmacogenomics, is proposed. The results show that the model compares favorably with the linear models in terms of prediction and explaining the variations in warfarin dosing.

Subject Keywords

Bayesian structural equation modeling, Data mining, Personalized medicine, Pharmacogenomics

URI

https://hdl.handle.net/11511/32170

Journal

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS

DOI

https://doi.org/10.1109/jbhi.2014.2336974

Collections

Graduate School of Informatics, Article

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Citation Formats

S. M. Oztaner, T. Taşkaya Temizel, S. R. Erdem, and M. ÖZER, “A Bayesian Estimation Framework for Pharmacogenomics Driven Warfarin Dosing: A Comparative Study,” IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, pp. 1724–1733, 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/32170.