A Machine Learning Approach to Predict Interdose Vancomycin Exposure
Author:
Publisher
Springer Science and Business Media LLC
Subject
Pharmacology (medical),Organic Chemistry,Pharmaceutical Science,Pharmacology,Molecular Medicine,Biotechnology
Link
https://link.springer.com/content/pdf/10.1007/s11095-022-03252-8.pdf
Reference20 articles.
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2. Uster DW, Stocker SL, Carland JE, Brett J, Marriott DJE, Day RO, et al. A model averaging/selection approach improves the predictive performance of model-informed precision dosing: vancomycin as a case study. Clin Pharmacol Ther. 2021;109:175–83.
3. Chen T, Guestrin C (2016) XGBoost: A Scalable Tree Boosting System. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD ‘16;785–94
4. Woillard J-B, Labriffe M, Debord J, Marquet P. Mycophenolic acid exposure prediction using machine learning. Clinical Pharmacology & Therapeutics 2021;
5. Woillard J-B, Labriffe M, Debord J, Marquet P. Tacrolimus exposure prediction using machine learning. Clin Pharmacol Ther 2020
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