Cardiovascular

Acute Coronary Syndrome

Latest AI and machine learning research in acute coronary syndrome for healthcare professionals.

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Showing 295-315 of 6,674 articles
Using Artificial Intelligence to Manage Thrombosis Research, Diagnosis, and Clinical Management.

Thrombosis development in either arterial or venous system remains a major cause of death and disabi...

Artificial Intelligence for Diagnosis of Acute Coronary Syndromes: A Meta-analysis of Machine Learning Approaches.

BACKGROUND: Machine learning (ML) encompasses a wide variety of methods by which artificial intellig...

Multi-Objective Optimization for Personalized Prediction of Venous Thromboembolism in Ovarian Cancer Patients.

Thrombotic events are one of the leading causes of mortality and morbidity related to cancer, with o...

Automated Detection of Vulnerable Plaque for Intravascular Optical Coherence Tomography Images.

PURPOSE: Vulnerable plaque detection is important to acute coronary syndrome (ACS) diagnosis. In rec...

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...

Reaffirmation of the importance of follow-up ultrasound studies in patients with high D-dimers and clinical suspicion of vein thrombosis.

BACKGROUND: Venous thromboembolism is a common disease seen in the emergency department and a cause ...

A Diagnostic Prediction Model of Acute Symptomatic Portal Vein Thrombosis.

BACKGROUND: The aim of this study was to develop a diagnostic prediction model to improve identifica...

Is Cardiac Troponin I Valuable to Detect Low-Level Myocardial Damage in Congestive Heart Failure?

OBJECTIVES: Congestive heart failure (CHF) is a heart disease with a growing incidence and prevalenc...

A Machine Learning-Based Approach for the Prediction of Acute Coronary Syndrome Requiring Revascularization.

The aim of this study is to predict acute coronary syndrome (ACS) requiring revascularization in tho...

Adjusting the dose in paediatric care: dispersing four different aspirin tablets and taking a proportion.

OBJECTIVES: When caring for children in a hospital setting, tablets are often manipulated at the war...

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...

Extensive phenotype data and machine learning in prediction of mortality in acute coronary syndrome - the MADDEC study.

Investigation of the clinical potential of extensive phenotype data and machine learning (ML) in th...

Specific impact of past and new major cardiovascular events on acute kidney injury and end-stage renal disease risks in diabetes: a dynamic view.

BACKGROUND: Interconnections between major cardiovascular events (MCVEs) and renal events are recogn...

Evidential MACE prediction of acute coronary syndrome using electronic health records.

BACKGROUND: Major adverse cardiac event (MACE) prediction plays a key role in providing efficient an...

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...

Utilizing dynamic treatment information for MACE prediction of acute coronary syndrome.

BACKGROUND: Main adverse cardiac events (MACE) are essentially composite endpoints for assessing saf...

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