Latest AI and machine learning research in myocardial infarction for healthcare professionals.
Digital twin technology, which enables the creation of patient-specific virtual models, is increasin...
BACKGROUND: Up to 50% of patients presenting with ST-elevation myocardial infarction (STEMI) have mu...
BACKGROUND AND OBJECTIVE: Artificial Intelligence (AI) models for electrocardiogram (ECG) interpreta...
Recent debates have focused on the impact of analytical imprecision in high-sensitivity cardiac trop...
AIMS: Acute myocardial infarction (AMI) remains a leading global cause of mortality, where timely di...
AIMS: Electrocardiograms (ECGs) and troponin (Tn) testing are essential tools for the diagnosis and ...
BACKGROUND: Many medications are associated with long QTc. Current long QTc predictors have limited ...
PURPOSE: This study aims to develop real-time phase-contrast (PC) cardiovascular MRI with low latenc...
BACKGROUND: Major depressive disorder (MDD) is prevalent and poses major public health implications....
Cardiovascular disease (CVD) is the top cause of mortality globally, making it crucial to diagnose a...
BACKGROUND: Early prediction of atrial fibrillation (AF) is crucial for reducing adverse outcomes. W...
Complex-valued neural networks (CVNNs) are particularly suitable for handling phase-sensitive signal...
Atrial fibrillation (AFIB) and ventricular fibrillation (VFIB) are two critical cardiovascular disea...
BACKGROUND: Timely detection and monitoring of abdominal aortic aneurysms (AAAs) are necessary to pr...
Heart arrhythmias are one of the most important categories of cardiovascular illness. A heartbeat th...
Determination of cardiac output (CO) is essential to the clinical management of cardiovascular compr...
This study aims to develop a multimodal driver emotion recognition system that accurately identifies...
INTRODUCTION: Bleeding is a serious complication in cardiac surgery, especially among patients recei...
Perinatology relies on continuous engagement with an expanding body of clinical literature, yet the ...
Current machine learning-based (ML) models usually attempt to utilize all available patient data to ...
BACKGROUND: Given the challenges faced during percutaneous coronary intervention (PCI) for heavily c...