Evaluation of supervised machine learning algorithms in predicting the poor anticoagulation control and stable weekly doses of warfarin
Author:
Funder
AGU RCSI
Publisher
Springer Science and Business Media LLC
Subject
Pharmacology (medical),Pharmaceutical Science,Pharmacology,Toxicology,Pharmacy
Link
https://link.springer.com/content/pdf/10.1007/s11096-022-01471-y.pdf
Reference39 articles.
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2. Loebstein R, Yonath H, Peleg D, et al. Interindividual variability in sensitivity to warfarin-Nature or nurture? Clin Pharmacol Ther. 2001;70(2):159–64.
3. Yang W, Ma J, Hu W, et al. Associated factors and safety of the rapidly achieving first therapeutic target of warfarin in hospitalized patients: a retrospective cohort study. Int J Clin Pharm. 2022. https://doi.org/10.1007/s11096-022-01404-9.
4. Sridharan K, Al Banny R, Qader AM, et al. Health-related quality of life in patients receiving oral anti-coagulants: a cross-sectional study. Expert Rev Cardiovasc Ther. 2020;18(5):309–14.
5. Bader LA, Elewa H. The impact of genetic and non-genetic factors on warfarin dose prediction in MENA region: a systematic review. PLoS ONE. 2016;11(12):e0168732.
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