Cardiovascular

Arrhythmias

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

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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...

Prediction of Pulmonary Vein Isolation and Gap Recurrence on 12-Lead ECG Using Deep Learning

Pulmonary vein isolation (PVI) is key to atrial fibrillation (AF) ablation, but arrhythmia often rec...

A Fast, Lightweight, and Generalizable Deep Neural Network for the Detection of Atrial Fibrillation

Atrial fibrillation (AFib) represents a critical diagnostic challenge in clinical cardiology, callin...

Artificial Intelligence for Significant Mitral Regurgitation Screening and Diagnosis: A Systematic Review and Meta-analysis

To evaluate performance of artificial intelligence (AI) models using electrocardiogram (ECG) and ech...

Comparing different types of machine learning models in diagnosing diabetes mellitus utilizing electrocardiography and clinical data

Diabetes Mellitus (DM) represents one of the most significant global public health challenges of the...

CardioForest: An Explainable Ensemble Learning Model for Automatic Wide QRS Complex Tachycardia Diagnosis from Ecg *

This study aims to develop and evaluate an ensemble machine learning-based framework for the automat...

Reliability of Artificial Intelligence-enhanced Electrocardiography

The scientific literature on artificial intelligence-enabled electrocardiography (AI-ECG) has define...

A Comparative Analysis of Supervised and Unsupervised Learning Methods for Normal-Abnormal Heartbeat Classification

In this study, the performances of 33 supervised and unsupervised machine learning methods for the a...

Deep Learning Driven Field Dose Prediction for Head and Neck Cancer Treated with Spot Scanning Proton Therapy

Accurate dose prediction is essential for automating radiotherapy planning. In spot scanning proton ...

Artificial Intelligence-Enhanced Electrocardiogram Models for Detection of Left Ventricular Dysfunction: A Comparison Study

Several artificial intelligence-enhanced electrocardiogram (AI-ECG) models have shown promise in det...

Long-term, ambulatory 12-lead ECG from a single non-standard lead using perceptual reconstruction

Despite its broadening indications, the implantable cardiac monitor (ICM) records a narrow, nonstand...

Artificial intelligence-driven ECG biomarkers for screening of large pericardial effusion

Pericardial effusion can progress to life-threatening cardiac tamponade when large or rapidly accumu...

An Artificial Intelligence Model for Detection of Heart Failure with Preserved Ejection Fraction: A Report from HeartShare Study

Heart failure with preserved ejection fraction (HFpEF) accounts for over half of all heart failure c...

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