Cardiovascular

Venous Thrombosis

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

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Showing 127-147 of 1,841 articles
Development of neuro-fuzzy model to explore gene-nutrient interactions modulating warfarin dose requirement.

AIM: To investigate the influence of alterations in vitamin K (K1, K2 and K3) in modulating warfarin...

Artificial neural network-based pharmacogenomic algorithm for warfarin dose optimization.

AIM: To develop more precise pharmacogenomic algorithm for prediction of safe and effective dose of ...

Danhong huayu koufuye prevents deep vein thrombosis through anti-inflammation in rats.

BACKGROUND: Danhong huayu koufuye (DHK) has traditionally been used clinically for a long time in Ch...

Clinical implication of monitoring rivaroxaban and apixaban by using anti-factor Xa assay in patients with non-valvular atrial fibrillation.

BACKGROUND: Although patients taking non-vitamin K antagonist oral anticoagulants (NOACs) do not req...

Seminal Plasma Heparin Binding Proteins Improve Semen Quality by Reducing Oxidative Stress during Cryopreservation of Cattle Bull Semen.

Heparin binding proteins (HBPs) are produced by accessory glands. These are secreted into the semina...

Association between inflammation biomarkers, anatomic extent of deep venous thrombosis, and venous symptoms after deep venous thrombosis.

OBJECTIVE: Inflammation may play a role in pathogenesis of venous thromboembolism, but the nature of...

Revisiting Warfarin Dosing Using Machine Learning Techniques.

Determining the appropriate dosage of warfarin is an important yet challenging task. Several predict...

A novel method of adverse event detection can accurately identify venous thromboembolisms (VTEs) from narrative electronic health record data.

BACKGROUND: Venous thromboembolisms (VTEs), which include deep vein thrombosis (DVT) and pulmonary e...

Anticoagulation colloidal microrobots based on heparin-mimicking polymers.

Coagulation within blood vessels is a major cause of cardiovascular disease and global mortality, hi...

Bleeding risk assessment tools in patients with atrial fibrillation taking anticoagulants: a comparative review and clinical implications.

INTRODUCTION: Bleeding risk assessment plays a critical role in the anticoagulation management for a...

Novel AI Guided Non-Expert Compression Ultrasound DVT Diagnostic Pathway May Reduce Vascular Laboratory Venous Testing .

OBJECTIVE: Ultrasonography and D-dimer testing are established modalities for evaluating potential l...

Applying Machine Learning for Prescriptive Support: A Use Case with Unfractionated Heparin in Intensive Care Units.

Continuous unfractionated heparin is widely used in intensive care, yet its complex pharmacokinetic ...

Innovative approaches to atrial fibrillation prediction: should polygenic scores and machine learning be implemented in clinical practice?

Atrial fibrillation (AF) prediction and screening are of important clinical interest because of the ...

[Construction of a back propagation neural network model for predicting urosepsis after flexible ureteroscopic lithotripsy].

OBJECTIVES: To analyze the association of serum heparin-binding protein (HBP) and C-reactive protein...

Efficacy of Intraoperative Cell Salvage on Perioperative Blood Transfusion in Pelvic and Acetabular Surgery: A Matched Cohort Analysis.

BACKGROUND: Pelvic fractures often result in traumatic and intraoperative blood loss. Cell salvage (...

Skin Changes in Suspected Lyme Disease.

Dear Editor, Ticks carry many diseases, bacteria, and viruses and represent a very important healthc...

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