Cardiovascular

Venous Thrombosis

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

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Showing 64-84 of 1,841 articles
Outcomes from a prospectively implemented protocol using apixaban after robot-assisted radical cystectomy.

OBJECTIVES: To compare the safety and efficacy of oral apixaban with that of injectable enoxaparin a...

CG02N Analyzer Accurately Measures Fibrinogen Level in Whole Blood in the Presence of Low- or High-Dose Heparin.

Rapid fibrinogen (Fbg) evaluation is important in patients with massive bleeding during severe traum...

Deep learning on graphs for multi-omics classification of COPD.

Network approaches have successfully been used to help reveal complex mechanisms of diseases includi...

Simultaneous excision of pelvic lipoma and robot-assisted radical prostatectomy.

Lipoma is a benign mesenchymal tumour that can develop in any part of the body containing adipose ti...

Automated warfarin dose prediction for Asian, American, and Caucasian populations using a deep neural network.

Existing warfarin dose prediction algorithms based on pharmacogenetics and clinical parameters have ...

How do I/we forecast tomorrow's transfusion? A focus on recipients' profiles.

Red blood cell (RBC) transfusion is a life-saving medical intervention and has an essential role in ...

Comparison of Higher-Than-Standard to D-Dimer Driven Thromboprophylaxis in Hospitalized Patients With COVID-19.

Coronavirus disease 2019 is a global health threat often accompanied with coagulopathy. Despite use...

Determining the adjusted initial treatment dose of warfarin anticoagulant medicine using kernel-based support vector regression.

BACKGROUND AND OBJECTIVE: A novel research field in bioinformatics is pharmacogenomics and the corre...

Evaluation of Unfractionated Heparin Dosing by Antifactor Xa During Targeted Temperature Management Post Cardiac Arrest.

PURPOSE: To evaluate unfractionated heparin (UFH) dosing guided by antifactor Xa levels during targe...

Machine Learning: An Overview and Applications in Pharmacogenetics.

This narrative review aims to provide an overview of the main Machine Learning (ML) techniques and t...

Deep Semantic Segmentation Feature-Based Radiomics for the Classification Tasks in Medical Image Analysis.

Recently, an emerging trend in medical image classification is to combine radiomics framework with d...

Development of a system to support warfarin dose decisions using deep neural networks.

The first aim of this study was to develop a prothrombin time international normalized ratio (PT INR...

Prediction of venous thromboembolism with machine learning techniques in young-middle-aged inpatients.

Accumulating studies appear to suggest that the risk factors for venous thromboembolism (VTE) among ...

Systematic review of machine learning models for personalised dosing of heparin.

AIM: To identify and critically appraise studies of prediction models, developed using machine learn...

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