Cardiovascular

Venous Thrombosis

Latest AI and machine learning research in venous thrombosis for healthcare professionals.

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Showing 1-21 of 3,312 articles
Dual-energy computed tomography pulmonary angiography for pulmonary embolism: a three-tier evidence framework to guide individualized low-iodine scanning.

Dual-energy computed tomography (DECT) pulmonary angiography (CTPA) is widely studied for pulmonary ...

(4)
Oct 2026 42886026
An Explainable Machine Learning Model Integrating Clinical Parameters for Identifying Left Atrial Appendage Thrombus in Non-valvular Atrial Fibrillation.

OBJECTIVE: This study aimed to develop a predictive model for left atrial appendage thrombus (LAAT) ...

(2)
Oct 2026 42855401
Artificial Intelligence-Derived Electrocardiographic Age Enhances Stroke Risk Stratification in Patients With Atrial Fibrillation With a CHA2DS2-VA Score of 1.

BACKGROUND: To evaluate whether artificial intelligence-derived electrocardiographic-age enhances th...

(4)
Sep 2026 42808453
Conceptualizing the Future of Thromboprophylaxis for Hospitalized Children.

The practice of thromboprophylaxis in hospitalized children is evolving. Emerging research in pediat...

(1)
Sep 2026 42772687
Obstetric pharmacoeconomics.

INTRODUCTION: Pharmacoeconomic principles are increasingly shaping modern obstetric pharmacology as ...

(5)
Sep 2026 42765528
On-Premise Detection of a Guideline-Driven Oral Anticoagulation Shift in German Doctors' Letters Using Local Large Language Models.

INTRODUCTION: A vast amount of German clinical routine data are still stored in unstructured doctors...

Sep 2026 42752478
Machine Learning and Deep Learning in Deep Vein Thrombosis: A Narrative Review of Clinical Applications for Diagnosis, Risk Prediction, and Outcome Management.

Machine learning (ML) and deep learning (DL) are increasingly applied across the clinical spectrum o...

(1)
Sep 2026 42753806
Dynamic Simulation and Digital Twins in Atrial Fibrillation: Complementary Roles and Current Limitations.

Atrial fibrillation (AF) management relies on established risk scores, with CHA2DS2-VASc supporting ...

(1)
Sep 2026 42754093
Predicting unplanned CRRT interruptions in critically Ill burn patients using stacked ensemble machine learning framework.

Unplanned interruption of continuous renal replacement therapy (CRRT) is a frequent complication in ...

(3)
Sep 2026 42730639
Advances from Traditional Clinical Decision Support Tools to Machine Learning Applications in Primary Prevention of Thromboembolic Disorders.

Primary thromboprophylaxis for arterial and venous thromboembolism (VTE) still presents many challen...

(1)
Sep 2026 42716101
Post AF Ablation Anticoagulation: Real World Practice and Predictors of Therapy.

BACKGROUND: Oral anticoagulation (OAC) is recommended for ≥3 months post catheter ablation (CA) for ...

(2)
Sep 2026 42705569
AI-Powered, Temperature-Resolved Centrifugal Microfluidics for Rapid 3D Phase-Diagram Generation of Biomolecular Condensates.

Biomolecular phase separation drives the formation of membraneless organelles and is implicated in n...

(2)
Aug 2026 42675591
Development and Validation of the GLORIA-AF Stroke Weighted Risk Score for Patients with Atrial Fibrillation.

BACKGROUND AND AIMS: Accurate stroke-risk stratification is central to anticoagulation decision-maki...

(3)
Aug 2026 42667264
Preserving Expertise in Vitamin K Antagonists in the Era of Direct Oral Anticoagulants: Avoiding Therapeutic Segregation.

The rapid uptake of direct oral anticoagulants (DOACs) has sharply reduced the prescribing of vitami...

(4)
Aug 2026 42665232
Recent advances and knowledge gaps in anticoagulation strategy with durable left ventricular assist devices.

Driven by technological advancements, donor shortages, and an aging population, utilization of left ...

(2)
Aug 2026 42550131
Small Intracerebral Hemorrhage: Baseline CT Edema-to-Hematoma Ratio as an Independent Predictor of Early Expansion.

BACKGROUND AND PURPOSE: Small intracerebral hemorrhage (ICH), defined as baseline NCCT hematoma volu...

(2)
Aug 2026 41741222
Decision-making logic for samples of clinically significant EDTA-dependent pseudothrombocytopenia with machine learning.

OBJECTIVES: To establish practical, clinically meaningful criteria for identifying significant plate...

(4)
Aug 2026 42624190
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