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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
Metadata
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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