Cardiovascular

Acute Coronary Syndrome

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

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Showing 22-42 of 6,674 articles
Thrombo-vera: a new thrombosis risk model for polycythemia vera using modern variable selection methods.

BACKGROUND: Thrombosis is a major complication in polycythemia vera (PV), contributing to significan...

Machine learning application for bleeding risk prediction in patients with atrial fibrillation treated with oral anticoagulation.

Atrial fibrillation (AF) is a prevalent cardiac arrhythmia associated with a significantly increased...

Accelerated MRI in temporomandibular joints using AI-assisted compressed sensing technique: a feasibility study.

OBJECTIVE: To investigate the feasibility of accelerated MRI with artificial intelligence-assisted c...

Towards prehospital risk stratification using deep learning for ECG interpretation in suspected acute coronary syndrome.

OBJECTIVES: Most patients presenting with chest pain in the emergency medical services (EMS) setting...

Incorporating the STOP-BANG questionnaire improves prediction of cardiovascular events during hospitalization after myocardial infarction.

Obstructive sleep apnea (OSA) may impact outcomes in acute coronary syndrome (ACS) patients. The Glo...

Development Of the VAMPCT Score for Predicting Mortality in CKD Patients with COVID-19.

Chronic kidney disease (CKD) patients with coronavirus disease 2019 (COVID-19) are at significant r...

A machine learning-based predictive model for the occurrence of lower extremity deep vein thrombosis after laparoscopic surgery in abdominal surgery.

BACKGROUND & AIMS: Deep vein thrombosis, a common complication after laparoscopic surgery, can negat...

Performance of convolutional neural network-enhanced electrocardiography in detecting acute coronary syndrome: focusing on subtypes and reduced leads.

BACKGROUND: Early and accurate diagnosis of acute coronary syndrome (ACS), particularly non-ST-eleva...

Improving ACS prediction in T2DM patients by addressing false records in electronic medical records using propensity score.

Our study aims to improve the prediction performance of machine learning (ML) models by addressing f...

Predicting Aboveground Carbon Storage in Different Types of Forests in South Subtropical Regions Using Machine Learning Models.

Motivated by the need to enhance the accuracy of forest aboveground carbon storage (ACS) assessments...

AI-Based Predictive Models for Cardiogenic Shock in STEMI: Real-World Data for Early Risk Assessment and Prognostic Insights.

Cardiogenic shock (CS) is a life-threatening complication of ST-elevation myocardial infarction (ST...

Dynamic Predictive Models of Cardiogenic Shock in STEMI: Focus on Interventional and Critical Care Phases.

: While early risk stratification in STEMI is essential, the threat of cardiogenic shock (CS) persis...

Direct evaluation of antiplatelet therapy in coronary artery disease by comprehensive image-based profiling of circulating platelets.

Coronary artery disease (CAD) is a leading cause of death globally. Antiplatelet therapy remains cru...

Impact of body mass index on D-dimer diagnostic utility for deep vein thrombosis in patients with cancer: a single-center retrospective analysis.

BACKGROUND: Deep vein thrombosis (DVT) is a common complication in cancer patients associated with s...

Using machine learning models to predict post-revascularization thrombosis in PAD.

BACKGROUND: Graft/ stent thrombosis after lower extremity revascularization (LER) is a serious compl...

Invited Article: Al guided Dual Antiplatelet Therapy and Anticoagulation.

Artificial intelligence (AI) has emerged as a transformative tool in healthcare through data analysi...

Artificial intelligence guided imaging as a tool to fill gaps in health care delivery.

Deep vein thrombosis (DVT) causes significant morbidity/mortality and timely diagnosis often via ult...

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