Cardiovascular

Arrhythmias

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

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Showing 1513-1533 of 2,005 articles
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...

Early Detection of Cardiovascular Disease Risk Using Multi-Parameter Biomarker Analysis and Machine Learning: A Prospective Cohort Study

Cardiovascular disease (CVD) remains the leading cause of mortality globally, with many events occur...

Deep learning enhanced magnetocardiography enables multi-task detection of coronary, ventricular, and rhythm disorders

Magnetocardiography (MCG) captures the magnetic fields generated by myocardial currents, theoretical...

Automatic quantification of left atrium volume for cardiac rhythm analysis leveraging 3D residual UNet for time-varying segmentation of ECG-gated CT.

Atrial fibrillation (AF) is a heart condition widely recognized as a significant risk factor for str...

Jan 2025 40487246
Enhancing ECG disease detection accuracy through deep learning models and P-QRS-T waveform features.

Cardiovascular diseases (CVDs) have surpassed cancer and become the major cause of death worldwide. ...

Jan 2025 40493615
Transfer learning in ECG diagnosis: Is it effective?

The adoption of deep learning in ECG diagnosis is often hindered by the scarcity of large, well-labe...

Jan 2025 40388401
A Systematic Review on the Effectiveness of Machine Learning in the Detection of Atrial Fibrillation.

Recent endeavors have led to the exploration of Machine Learning (ML) to enhance the detection and a...

Jan 2025 39092649
Evaluating gradient-based explanation methods for neural network ECG analysis using heatmaps.

OBJECTIVE: Evaluate popular explanation methods using heatmap visualizations to explain the predicti...

Jan 2025 39504476
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