Myocardial Infarction

Latent Class Analysis Identifies Distinct Patient Phenotypes Associated With Mistaken Treatment Decisions and Adverse Outcomes in Coronary Artery Disease.

This study aimed to identify patient characteristics linked to mistaken treatments and major adverse...

Risk Stratification of CABG Patients Using an Artificial Intelligence ECG-Derived Age.

OBJECTIVE: To assess the prognostic value of artificial intelligence electrocardiogram-derived (AI E...

Comparing the Performance of Machine Learning Models and Conventional Risk Scores for Predicting Major Adverse Cardiovascular Cerebrovascular Events After Percutaneous Coronary Intervention in Patients With Acute Myocardial Infarction: Systematic Review and Meta-Analysis.

BACKGROUND: Machine learning (ML) models may offer greater clinical utility than conventional risk s...

Electrocardiographic sex index: a continuous representation of sex.

Clinical risk calculators consider sex as a binary variable. However, sex is a complex trait with an...

Monitoring systemic ventriculoarterial coupling after cardiac surgery using continuous transoesophageal echocardiography and deep learning.

Deterioration of ventriculoarterial coupling is detrimental to cardiovascular and left ventricular f...

Artificial intelligence-enhanced electrocardiography to predict regurgitant valvular heart diseases: an international study.

BACKGROUND AND AIMS: Valvular heart disease (VHD) is a significant source of morbidity and mortality...

A Lightweight ML-Based ECG Classification System using Self-Personalized Anomaly Detector.

Targeting the real-time arrhythmia diagnosis on resource-limited edge devices, in this paper, we pre...

Construction of a Machine Learning-Based Clopidogrel Resistance Risk Prediction Model.

Clopidogrel is extensively utilized for the prevention and treatment of cardiovascular, cerebrovascu...

Prediction of Percutaneous Coronary Intervention Success in Patients With Moderate to Severe Coronary Artery Calcification Using Machine Learning Based on Coronary Angiography: Prospective Cohort Study.

BACKGROUND: Given the challenges faced during percutaneous coronary intervention (PCI) for heavily c...

ModelS4Apnea: leveraging structured state space models for efficient sleep apnea detection from ECG signals.

. Sleep apnea is a common sleep disorder associated with severe health risks, necessitating accurate...

Fusion of Personalized Federated Learning (PFL) with Differential Privacy (DP) Learning for Diagnosis of Arrhythmia Disease.

This paper presents a novel privacy-preserving architecture, a fusion of Federated Learning with Per...

Inflammatory, fibrotic and endothelial biomarker profiles in COVID-19 patients during and following hospitalization.

Survivors of severe COVID-19 often suffer from long-term respiratory issues, but the molecular drive...

Artificial intelligence-enhanced ECG detection of acute coronary occlusion in chest pain patients with ST-elevation in lead aVR - A direct comparison to conventional ECG criteria.

Efficient pretraining of ECG scalogram images using masked autoencoders for cardiovascular disease diagnosis.

Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide, emphasizing the need fo...

Artificial intelligence in cardiac sarcoidosis: ECG, Echo, CPET and MRI.

PURPOSE OF REVIEW: Cardiac sarcoidosis is a form of inflammatory cardiomyopathy that varies in its c...

Enhancing automatic multilabel diagnosis of electrocardiogram signals: A masked transformer approach.

BACKGROUND AND OBJECTIVE: Electrocardiogram (ECG) is one of the most important diagnostic tools in c...

AI-ECG for early detection of atrial fibrillation: First-year results from a stroke prevention study in Shimizu, Japan.

BACKGROUND: An artificial intelligence algorithm-guided electrocardiogram (AI-ECG) has been develope...

Artificial intelligence for electrocardiographic diagnosis of perioperative myocardial ischaemia: a scoping review.

BACKGROUND: Perioperative electrocardiographic monitoring can offer immediate detection of myocardia...

Efficient sleep apnea detection using single-lead ECG: A CNN-Transformer-LSTM approach.

BACKGROUND: Sleep apnea (SA), a prevalent sleep-related breathing disorder, disrupts normal respirat...

Artificial Intelligence-Enabled ECGs for Atrial Fibrillation Identification and Enhanced Oral Anticoagulant Adoption: A Pragmatic Randomized Clinical Trial.

BACKGROUND: Atrial fibrillation (AF) is often underdiagnosed and undertreated by noncardiologists. T...

Semantic ECG hash similarity graph.

Graph-based methods have made significant progress in addressing the dependent correlations among EC...