Arrhythmias

Comparison of Machine Learning Detection of Low Left Ventricular Ejection Fraction Using Individual ECG Leads.

The 12-lead electrocardiogram (ECG) is the most common front-line diagnosis tool for assessing cardi...

Validation of an automated artificial intelligence system for 12‑lead ECG interpretation.

BACKGROUND: The electrocardiogram (ECG) is one of the most accessible and comprehensive diagnostic t...

Race, Sex, and Age Disparities in the Performance of ECG Deep Learning Models Predicting Heart Failure.

BACKGROUND: Deep learning models may combat widening racial disparities in heart failure outcomes th...

Applying Recurrent Neural Networks for Anomaly Detection in Electrocardiogram Sensor Data.

Monitoring heart electrical activity is an effective way of detecting existing and developing condit...

SEResUTer: a deep learning approach for accurate ECG signal delineation and atrial fibrillation detection.

Accurate detection of electrocardiogram (ECG) waveforms is crucial for computer-aided diagnosis of c...

Improving Valvular Pathologies and Ventricular Dysfunction Diagnostic Efficiency Using Combined Auscultation and Electrocardiography Data: A Multimodal AI Approach.

Simple sensor-based procedures, including auscultation and electrocardiography (ECG), can facilitate...

Personalized ECG monitoring and adaptive machine learning.

This non-technical review introduces key concepts in personalized ECG monitoring (pECG), which aims ...

Deep learning-based dynamic ventilatory threshold estimation from electrocardiograms.

BACKGROUND AND OBJECTIVE: The ventilatory threshold (VT) marks the transition from aerobic to anaero...

Artificial intelligence-enhanced electrocardiogram for arrhythmogenic right ventricular cardiomyopathy detection.

AIMS: ECG abnormalities are often the first signs of arrhythmogenic right ventricular cardiomyopathy...

Impact of automatic acquisition of key clinical information on the accuracy of electrocardiogram interpretation: a cross-sectional study.

BACKGROUND: The accuracy of electrocardiogram (ECG) interpretation by doctors are affected by the av...

Deep learning-based regional ECG diagnosis platform.

OBJECTIVE: To enable the intelligent diagnosis of a variety of common Electrocardiogram (ECG), we in...

ECG-Based Multiclass Arrhythmia Classification Using Beat-Level Fusion Network.

Cardiovascular disease (CVD) is one of the most severe diseases threatening human life. Electrocardi...

General anesthesia enhances lesion quality and ablation efficiency of circumferential pulmonary vein isolation.

BACKGROUND: Pulmonary vein isolation (PVI) is the cornerstone of atrial fibrillation (AF) ablation. ...

Deep learning with fetal ECG recognition.

Independent component analysis (ICA) is widely used in the extraction of fetal ECG (FECG). However, ...

Conversion to Sinus Rhythm in Refractory Atrial Fibrillation Patients after Atrioventricular Node Ablation with Conduction System Pacing.

BACKGROUND: "Ablate and pace" strategy is a reasonable treatment option in refractory atrial fibrill...

Deep learning-based NT-proBNP prediction from the ECG for risk assessment in the community.

OBJECTIVES: The biomarker N-terminal pro B-type natriuretic peptide (NT-proBNP) has predictive value...

Wavelet transform and deep learning-based obstructive sleep apnea detection from single-lead ECG signals.

Sleep apnea is a common sleep disorder. Traditional testing and diagnosis heavily rely on the expert...

Predictive Value of Machine Learning for Recurrence of Atrial Fibrillation after Catheter Ablation: A Systematic Review and Meta-Analysis.

BACKGROUND: Accurate detection of atrial fibrillation (AF) recurrence after catheter ablation is cru...

Artificial intelligence-enabled 8-lead ECG detection of atrial septal defect among adults: a novel diagnostic tool.

BACKGROUND: Patients with atrial septal defect (ASD) exhibit distinctive electrocardiogram (ECG) pat...

Moving From PQRST to AI: Advancing Transparency, Reliability, and Clinical Translation in ECG Deep Learning.

Clinical Applications, Methodology, and Scientific Reporting of Electrocardiogram Deep-Learning Models: A Systematic Review.

BACKGROUND: The electrocardiogram (ECG) is one of the most common diagnostic tools available to asse...