AIMC Topic: Anticoagulants
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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...
Anticoagulation colloidal microrobots based on heparin-mimicking polymers.
Journal of colloid and interface science
Mar 19, 2025
Coagulation within blood vessels is a major cause of cardiovascular disease and global mortality, highlighting the urgent need for effective anticoagulant strategies. In this study, we introduce a dynamic and highly efficient anticoagulant platform, ...
Machine Learning Predicts Bleeding Risk in Atrial Fibrillation Patients on Direct Oral Anticoagulant.
The American journal of cardiology
Feb 25, 2025
Predicting major bleeding in nonvalvular atrial fibrillation (AF) patients on direct oral anticoagulants (DOACs) is crucial for personalized care. Alternatives like left atrial appendage closure devices lower stroke risk with fewer nonprocedural blee...
Causal Machine Learning for Left Atrial Appendage Occlusion in Patients With Atrial Fibrillation.
JACC. Clinical electrophysiology
Feb 12, 2025
BACKGROUND: Transcatheter left atrial appendage occlusion (LAAO) is an alternative to lifelong anticoagulation, but optimal patient selection remains challenging.
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...
Development of Machine-learning Model to Predict Anticoagulant Use and Type in Geriatric Traumatic Brain Injury Using Coagulation Parameters.
Neurologia medico-chirurgica
Dec 25, 2024
This study aimed to investigate the patterns of anticoagulation therapy and coagulation parameters and to develop a prediction model to predict the type of anticoagulation therapy in geriatric patients with traumatic brain injury. A retrospective ana...
Residual risk prediction in anticoagulated patients with atrial fibrillation using machine learning: A report from the GLORIA-AF registry phase II/III.
European journal of clinical investigation
Dec 11, 2024
BACKGROUND: Although oral anticoagulation decreases the risk of thromboembolism in patients with atrial fibrillation (AF), a residual risk of thrombotic events still exists. This study aimed to construct machine learning (ML) models to predict the re...
ROC Curve
Logistic Models
Ischemic Stroke
Area Under Curve
Humans
Anticoagulants
Machine Learning
Registries
Algorithms
Stroke
Myocardial Infarction
Aged, 80 and over
Male
Middle Aged
Female
Risk Assessment
Ischemic Attack, Transient
Thrombosis
Risk Factors
Thromboembolism
Administration, Oral
Aged
Atrial Fibrillation
From Code to Clots: Applying Machine Learning to Clinical Aspects of Venous Thromboembolism Prevention, Diagnosis, and Management.
Hamostaseologie
Dec 10, 2024
The high incidence of venous thromboembolism (VTE) globally and the morbidity and mortality burden associated with the disease make it a pressing issue. Machine learning (ML) can improve VTE prevention, detection, and treatment. The ability of this n...
Heparin in sepsis: current clinical findings and possible mechanisms.
Frontiers in immunology
Dec 6, 2024
Sepsis is a clinical syndrome resulting from the interaction between coagulation, inflammation, immunity and other systems. Coagulation activation is an initial factor for sepsis to develop into multiple organ dysfunction. Therefore, anticoagulant th...
A Machine Learning-Based Approach for the Prediction of Anticoagulant Activity of Hypericum perforatum L. and Evaluation of Compound Activity.
Phytochemical analysis : PCA
Nov 17, 2024
INTRODUCTION: Hypericum perforatum L. (HPL) is extensively researched domestically and internationally as a medicinal plant. However, no reports of studies related to the anticoagulant activity of HPL have been retrieved. The specific bioactive compo...
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