Cardiovascular

Venous Thrombosis

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

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Showing 85-105 of 1,841 articles
Continuous Infusion Low-Dose Unfractionated Heparin for the Management of Hypercoagulability Associated With COVID-19.

INTRODUCTION: The Coronavirus Disease 2019 (COVID-19) is associated with severe hypercoagulability. ...

Predicting Anticoagulation Need for Otogenic Intracranial Sinus Thrombosis: A Machine Learning Approach.

 The role of anticoagulation (AC) in the management of otogenic cerebral venous sinus thrombosis (O...

Efficacy of enoxaparin in preventing coagulation during high-flux haemodialysis, expanded haemodialysis and haemodiafiltration.

BACKGROUND: Low-molecular-weight heparins (LMWHs) are easily dialysable with high-flow membranes; ho...

Mechanical heart valves and pregnancy: Issues surrounding anticoagulation. Experience from two obstetric cardiac centres.

BACKGROUND: Pregnant women with mechanical heart valves are at significant risk of obstetric/cardiac...

Sulodexide modulates the dialysate effect on the peritoneal mesothelium.

Peritoneal membrane damage during chronic peritoneal dialysis is the main cause of that treatment fa...

Machine learning detection of Atrial Fibrillation using wearable technology.

BACKGROUND: Atrial Fibrillation is the most common arrhythmia worldwide with a global age adjusted p...

Investigating the use of data-driven artificial intelligence in computerised decision support systems for health and social care: A systematic review.

There is growing interest in the potential of artificial intelligence to support decision-making in ...

Machine Learning Algorithm for Predicting Warfarin Dose in Caribbean Hispanics Using Pharmacogenetic Data.

Despite some previous examples of successful application to the field of pharmacogenomics, the utili...

Predicting Chronic Subdural Hematoma Recurrence and Stroke Outcomes While Withholding Antiplatelet and Anticoagulant Agents.

The aging of the western population and the increased use of oral anticoagulation (OAC) and antipla...

Assessment of a Machine Learning Model Applied to Harmonized Electronic Health Record Data for the Prediction of Incident Atrial Fibrillation.

IMPORTANCE: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, and its early ...

Transcriptome analysis and identification of genes associated with chicken sperm storage duration.

The sperm storage tubules located in the mucosal folds of the uterovaginal junction (UVJ) are the pr...

[Predicting atrial fibrillation through a sinus-rhythm electrocardiogram; useful or not?].

In patients with cryptogenic stroke, the detection of atrial fibrillation (AF) is important, since i...

Multicenter experience with photoselective vaporization of the prostate on men taking novel oral anticoagulants.

OBJECTIVE: Photoselective vaporization of the prostate (PVP) is a widely performed surgical procedur...

Fully Automated Segmentation of Lower Extremity Deep Vein Thrombosis Using Convolutional Neural Network.

OBJECTIVE: Deep vein thrombosis (DVT) is a disease caused by abnormal blood clots in deep veins. Acc...

Quantification of apixaban in human plasma using ultra performance liquid chromatography coupled with tandem mass spectrometry.

Apixaban, an inhibitor of direct factor Xa, is used for the treatment of venous thromboembolic event...

The use of artificial neural network analysis can improve the risk-stratification of patients presenting with suspected deep vein thrombosis.

Artificial neural networks are machine-learning algorithms designed to analyse data without a pre-ex...

An Ensemble Model With Clustering Assumption for Warfarin Dose Prediction in Chinese Patients.

The prediction of daily stable warfarin dosage for a specific patient is difficult. To improve the p...

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