Latest AI and machine learning research in myocardial infarction for healthcare professionals.
OBJECTIVE: Current clinical guidelines for non-ST-segment elevation myocardial infarction (NSTEMI) emphasize the duration of dual antiplatelet therapy (DAPT) based on scores such as the Predicting Bleeding Complications in Patients Undergoing Stent Implantation and Subsequent Dual Antiplatelet Therapy (PRECISE-DAPT) score and the Dual Antiplatelet Therapy (DAPT) score. However, these anatomical an...
Virtual coronary intervention planning (VCIP) aims to optimize the hemodynamic outcomes of percutaneous coronary intervention (PCI) in patients with coronary stenosis. However, its clinical adoption remains constrained by the computational burden associated with evaluating numerous combinatorial intervention strategies, leading to time-consuming workflows and potentially suboptimal decisions in th...
BACKGROUND: MASLD is the most prevalent chronic liver disease worldwide, with pooled global prevalence estimates of approximately 30%. Current noninva...
BACKGROUND: Automated electrocardiogram (ECG) assessment tools to assist clinicians in diagnosis have improved substantially over the past decade; how...
BACKGROUND: Machine learning (ML) applications in clinical medicine are vulnerable to data leakage, particularly temporal leakage from post-diagnostic...
BACKGROUND: Hippocampal avoidance whole-brain radiotherapy (HA-WBRT) is used to treat brain metastases while preserving cognitive function by sparing ...
BACKGROUND: Early diagnosis of acute coronary syndromes (ACS) remains challenging because electrical, mechanical, and biochemical manifestations of my...
BACKGROUND: Diastolic dysfunction is common in patients with aortic stenosis and may influence outcomes following surgical aortic valve replacement. W...
AIMS: Pre-participation cardiovascular screening (PPS) is essential for preventing SCD in athletes, yet ECG interpretation requires expertise and rema...
Early identification of acute myocardial infarction (AMI) remains challenging, particularly in non-ST-segment elevation presentations and occluded myo...
IMPORTANCE: Transthyretin amyloid cardiomyopathy (ATTR-CM) is a treatable cause of heart failure, but diagnosis is often delayed. Accessible tools to ...
Multimodal physiological signal fusion-particularly electroencephalography (EEG) and electrocardiography (ECG)-is widely assumed to improve emotion re...
Asthma and chronic obstructive pulmonary disease (COPD) represent the two most prevalent chronic respiratory conditions worldwide, affecting hundreds ...
AIMS: We aimed to develop and validate echocardiography-based prediction models for light chain (AL) and transthyretin (ATTR) cardiac amyloidosis and ...
Seizure prediction is critically important, as it can help prevent serious injuries, improve quality of life, and potentially reduce the risk of SUDEP...
Driven by technological advancements, donor shortages, and an aging population, utilization of left ventricular assist devices (LVAD), both as a bridg...
INTRODUCTION: Artificial intelligence electrocardiogram (AI-ECG) interpretation has emerged as a promising approach to identify Brugada syndrome (BrS)...
BACKGROUND: Recent advances in deep learning have led to the development of ECG foundation models (ECG-FMs) trained with self-supervised learning, whi...
Coronary angiography is routinely acquired during invasive assessment of coronary artery disease, but its interpretation remains fragmented across vis...
BACKGROUND: Artificial intelligence-enhanced electrocardiography (AI-ECG) may support ECG interpretation, prioritization, and workflow efficiency. ECG...