AIMC Topic: Warfarin
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Establishing a Validation Framework of Treatment Discontinuation in Claims Data Using Natural Language Processing and Electronic Health Records.
Clinical pharmacology and therapeutics
Apr 8, 2025
Measuring medication discontinuation in claims data primarily relies on the gaps between prescription fills, but such definitions are rarely validated. This study aimed to establish a natural language processing (NLP)-based validation framework to ev...
Optimizing warfarin dosing in diabetic patients through BERT model and machine learning techniques.
Computers in biology and medicine
Jan 28, 2025
This study highlights the importance of evaluating warfarin dosing in diabetic patients, who require careful anticoagulation management. With rising rates of diabetes and cardiovascular diseases, understanding the factors influencing warfarin therapy...
Machine Learning-Assisted Biomass-Derived Carbon Dots as Fluorescent Sensor Array for Discrimination of Warfarin and Its Metabolites.
Langmuir : the ACS journal of surfaces and colloids
Jan 11, 2025
Warfarin (WAR), an effective oral anticoagulant, is of utmost importance in treating many diseases. Despite its significance, rapid and precise discrimination of WAR remains a formidable challenge, especially facing its structural analogs of metaboli...
Pleiotropic Effects of Direct Oral Anticoagulants in Chronic Heart Failure and Atrial Fibrillation: Machine Learning Analysis.
Molecules (Basel, Switzerland)
Jun 4, 2024
Oral anticoagulant therapy (OAT) for managing atrial fibrillation (AF) encompasses vitamin K antagonists (VKAs, such as warfarin), which was the mainstay of anticoagulation therapy before 2010, and direct-acting oral anticoagulants (DOACs, namely dab...
Warfarin-A natural anticoagulant: A review of research trends for precision medication.
Phytomedicine : international journal of phytotherapy and phytopharmacology
Feb 23, 2024
BACKGROUND: Warfarin is a widely prescribed anticoagulant in the clinic. It has a more considerable individual variability, and many factors affect its variability. Mathematical models can quantify the quantitative impact of these factors on individu...
Machine Learning Predicting Atrial Fibrillation as an Adverse Event in the Warfarin and Aspirin in Reduced Cardiac Ejection Fraction (WARCEF) Trial.
The American journal of medicine
Aug 21, 2023
BACKGROUND: Atrial fibrillation and heart failure commonly coexist due to shared pathophysiological mechanisms. Prompt identification of patients with heart failure at risk of developing atrial fibrillation would allow clinicians the opportunity to i...
Automated warfarin dose prediction for Asian, American, and Caucasian populations using a deep neural network.
Computers in biology and medicine
Jan 13, 2023
Existing warfarin dose prediction algorithms based on pharmacogenetics and clinical parameters have not been used clinically due to the absence of external validation, lack of assessment for clinical utility, and high risk of bias. Moreover, given th...
Determining the adjusted initial treatment dose of warfarin anticoagulant medicine using kernel-based support vector regression.
Computer methods and programs in biomedicine
Dec 17, 2021
BACKGROUND AND OBJECTIVE: A novel research field in bioinformatics is pharmacogenomics and the corresponding applications of artificial intelligence tools. Pharmacogenomics is the study of the relationship between genotype and responses to medical me...
Stable warfarin dose prediction in sub-Saharan African patients: A machine-learning approach and external validation of a clinical dose-initiation algorithm.
CPT: pharmacometrics & systems pharmacology
Dec 9, 2021
Warfarin remains the most widely prescribed oral anticoagulant in sub-Saharan Africa. However, because of its narrow therapeutic index, dosing can be challenging. We have therefore (a) evaluated and compared the performance of 21 machine-learning tec...
Development of a system to support warfarin dose decisions using deep neural networks.
Scientific reports
Jul 20, 2021
The first aim of this study was to develop a prothrombin time international normalized ratio (PT INR) prediction model. The second aim was to develop a warfarin maintenance dose decision support system as a precise warfarin dosing platform. Data of 1...
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