Latest AI and machine learning research in myocardial infarction for healthcare professionals.
The electrocardiogram is the pivotal triage instrument in suspected acute myocardial infarction, yet for three decades its interpretation has been reduced to a single feature: whether ST-segment elevation meets a fixed millimeter threshold. Approximately one-quarter to one-third of patients labeled non-ST-segment elevation myocardial infarction (NSTEMI) harbor total culprit artery occlusion at nex...
The electrocardiogram (ECG) is a cornerstone of cardiovascular care. Traditionally, it has relied on expert visual interpretation and rule-based systems to define the presence of disease. However, the integration of artificial intelligence (AI) has transformed the ECG into a high-dimensional biomarker capable of detecting signatures of both overt and subclinical disease. This review explores the h...
BACKGROUND: The differentiation of primary ischemic from secondary nonischemic T-wave inversion (TWI) on electrocardiograms (ECGs) presents a critical...
Electrocardiography (ECG) is a widely adopted modality for monitoring cardiac rate and rhythm and identifying various abnormalities of the cardiac ele...
Heart failure (HF) affects 11.8% of adults aged 65 and older, reducing quality of life and longevity. Preventing HF can reduce morbidity and mortality...
Electrocardiogram (ECG)-based diagnostics are pivotal in early cardiac disorder detection, yet existing models often fail to integrate temporal, spect...
BACKGROUND: Elderly patients are highly susceptible to drug-drug interaction (DDI)-induced liver injury, yet comprehensive real-world evidence remains...
For acute myocardial infarction (AMI) patients undergoing percutaneous coronary intervention (PCI), accurate prediction of intraoperative complication...
This research delivers a comprehensive future-oriented multi-dimensional drought appraisal for Tiruchirappalli District, Tamil Nadu, India, by inter-l...
BACKGROUND: Preoperative cardiovascular risk stratification is essential in noncardiac surgery, but conventional testing is frequently overused, incre...
BACKGROUND: Prognostic assessment in secondary care settings remains challenging and may influence clinical decision-making and follow-up. Artificial ...
BACKGROUND: Frailty is common yet underdiagnosed in elderly patients with atrial fibrillation (AF), worsening outcomes and complicating treatment. Tra...
AIMS: Social isolation (SI) is associated with a higher risk of cardiovascular disease (CVD). One mechanism linking SI and CVD is accelerated biologic...
BACKGROUND: Hypertrophic cardiomyopathy (HCM) is often diagnosed late, increasing avoidable risk and delaying treatment. Artificial intelligence (AI) ...
AIMS: Perioperative myocardial injury (PMI) is a frequent and often asymptomatic complication after non-cardiac surgery and is associated with increas...
OBJECTIVE: Deep learning has advanced electrocardiogram (ECG) analysis but remains difficult to interpret, limiting clinical adoption and electrophysi...
BACKGROUND: Cardiac amyloidosis (CA) is an under-recognized cause of left-ventricular hypertrophy (LVH) that is often misclassified as hypertrophic ca...
BACKGROUND: Mitral regurgitation (MR), one of the most common valvular heart diseases, poses ongoing challenges in risk stratification and timely inte...
In this paper, we present a powerful, compact electrocardiogram (ECG) classification algorithm for cardiac arrhythmia diagnosis that addresses the cur...
BACKGROUND: Low peak oxygen consumption (V̇O2) is associated with higher cardiovascular and all-cause mortality, while improvements in peak V̇O2 reduc...