Cardiovascular

Arrhythmias

Latest AI and machine learning research in arrhythmias for healthcare professionals.

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ECG classification with convolutional neural networks demonstrates resilience to sex-imbalances in data

Many ECG-AI models have been developed to predict a wide range of cardiovascular outcomes. The under...

Short-term Repeatability of Artificial Intelligence Estimated Electrocardiographic Age

Advancements in artificial intelligence have enabled estimation of cardiac age from raw ECG waveform...

Machine learning to classify left ventricular hypertrophy using ECG feature extraction by variational autoencoder

Traditional ECG criteria for left ventricular hypertrophy (LVH) have modest diagnostic yield. Develo...

Enhancing the Reliability of Resting ECGs via Deep Learning–Driven Motion Artifact Detection

This study presents a novel two-stage framework to enhance the reliability of resting electrocardiog...

A deep learning ECG model for localization of occlusion myocardial infarction

Rapid identification and localization of an acute coronary occlusion are vital to prevent myocardial...

Forecasting left ventricular systolic dysfunction in heart failure with artificial intelligence

Objective assessment of left ventricular function remains a key prognosticator that is used to guide...

BeatAI: BiomEtrics for Atrial Arrhythmia Tracking Using Artificial Intelligence

Postoperative atrial fibrillation (POAF) affects 20 to 50% of patients undergoing cardiac surgery an...

Privacy-Aware Federated nnU-Net for ECG Page Digitization

Deep neural networks can convert ECG page images into analyzable waveforms, yet centralized training...

Intelligent Decision Support System Facilitating Early Detection of Cardiovascular Disease

Cardiovascular disease (CVD) remains the primary cause of mortality worldwide, with higher fatality ...

A foundation transformer model with self-supervised learning for ECG-based assessment of cardiac and coronary function

The wide availability of labeled electrocardiogram (ECG) data has driven major advances in artificia...

Seeing the Aging Heart: Multimodal AI Quantifies Cardiac Biological Aging from Angiography, Echocardiography, and ECG

Cardiac biological aging results in vascular, structural, and electrical changes that account for ag...

An Explainable Advanced Electrocardiography Score for Diastolic Dysfunction - Derivation, Validation and Prognostic Performance

Diastolic dysfunction is a precursor to heart failure with preserved ejection fraction (HFpEF), and ...

Deep Learning Prediction of Left Atrial Structure and Function from 12-lead Electrocardiograms

Abnormal cardiac atrial structure and function (atrial cardiopathy)1 typically precedes atrial fibri...

Artificial Intelligence-Enabled Electrocardiogram for Elevated Left Ventricular Filling Pressure

Left ventricular filling pressure (LVFP) is associated with heart failure symptoms, a key prognostic...

Cardiac Classification with Multi-Scale Convolutional Neural Network From Paper ECG

In cardiology, the classification of electrocardiograms (ECGs) or heartbeats serves as a vital instr...

Deep learning on 3D ECG geometry predicts ischemia

Three-dimensional (3D) electrocardiography (ECG) is a recent methodological advance that extends the...

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