ArticleFrontiers in pharmacology2021
Machine Learning for Prediction of Stable Warfarin Dose in US Latinos and Latin Americans.
Article in Frontiers in pharmacology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Genomic Impacts of Biological Exposures.Journal of developmental biology · 2026Review
- Artificial intelligence and machine learning for precision warfarin dosing: a comprehensive narrative review.European journal of clinical pharmacology · 2026Review
- AI-WAR: a novel warfarin management software with a bidirectional LSTM dosing model improves time in therapeutic range.Frontiers in pharmacology · 2026Article
- Application of machine learning techniques for warfarin dosage prediction: a case study on the MIMIC-III dataset.PeerJ. Computer science · 2025Article
- The Application of Artificial Intelligence in Atrial Fibrillation Patients: From Detection to Treatment.Reviews in cardiovascular medicine · 2024Review
- Optimizing warfarin dosing for patients with atrial fibrillation using machine learning.Scientific reports · 2024Article
- Artificial intelligence, medications, pharmacogenomics, and ethics.Pharmacogenomics · 2024Article
- Local Ancestry-Informed Candidate Pathway Analysis of Warfarin Stable Dose in Latino Populations.Clinical pharmacology and therapeutics · 2023Article
- Improved stacking ensemble learning based on feature selection to accurately predict warfarin dose.Frontiers in cardiovascular medicine · 2023Article
- Comparison between Machine Learning and Multiple Linear Regression to Identify Abnormal Thallium Myocardial Perfusion Scan in Chinese Type 2 Diabetes.Diagnostics (Basel, Switzerland) · 2022Article
- Nonlinear Machine Learning in Warfarin Dose Prediction: Insights from Contemporary Modelling Studies.Journal of personalized medicine · 2022Article
- Long Short-Term Memory Network for Development and Simulation of Warfarin Dosing Model Based on Time Series Anticoagulant Data.Frontiers in cardiovascular medicine · 2022Article
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Authors and funding
19 authors.
Funding
Abstract
Populations used to create warfarin dose prediction algorithms largely lacked participants reporting Hispanic or Latino ethnicity. While previous research suggests nonlinear modeling improves warfarin dose prediction, this research has mainly focused on populations with primarily European ancestry. We compare the accuracy of stable warfarin dose prediction using linear and nonlinear machine learning models in a large cohort enriched for US Latinos and Latin Americans (ULLA). Each model was tested using the same variables as published by the International Warfarin Pharmacogenetics Consortium (IWPC) and using an expanded set of variables including ethnicity and warfarin indication. We utilized a multiple linear regression model and three nonlinear regression models: Bayesian Additive Regression Trees, Multivariate Adaptive Regression Splines, and Support Vector Regression. We compared each model's ability to predict stable warfarin dose within 20% of actual stable dose, confirming trained models in a 30% testing dataset with 100 rounds of resampling. In all patients (
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