Arrhythmias

Superiority of Classification Tree versus Cluster, Fuzzy and Discriminant Models in a Heartbeat Classification System.

This study presents a 2-stage heartbeat classifier of supraventricular (SVB) and ventricular (VB) be...

Arrhythmia ablation using the Amigo Robotic Remote Catheter System versus manual ablation: One year follow-up results.

Real-Time Patient-Specific ECG Classification by 1-D Convolutional Neural Networks.

GOAL: This paper presents a fast and accurate patient-specific electrocardiogram (ECG) classificatio...

An Automatic Subject-Adaptable Heartbeat Classifier Based on Multiview Learning.

In this paper, a novel subject-adaptable heartbeat classification model is presented, in order to ad...

Impact of catheter ablation with remote magnetic navigation on procedural outcomes in patients with persistent and long-standing persistent atrial fibrillation.

BACKGROUND: The objectives of this study were to assess the procedural outcomes of persistent and lo...

Automatic diagnosis of premature ventricular contraction based on Lyapunov exponents and LVQ neural network.

Premature ventricular contraction (PVC) is a common type of abnormal heartbeat. Without early diagno...

ECG Prediction Based on Classification via Neural Networks and Linguistic Fuzzy Logic Forecaster.

The paper deals with ECG prediction based on neural networks classification of different types of ti...

Robotic ablation of atrial fibrillation.

BACKGROUND: Pulmonary vein isolation (PVI) is an established treatment for atrial fibrillation (AF)....

Automatic supporting system for regionalization of ventricular tachycardia exit site in implantable defibrillators.

Electrograms stored in Implantable Cardioverter Defibrillators (ICD-EGM) have been proven to convey ...

A Novel Algorithm for the Automatic Detection of Sleep Apnea From Single-Lead ECG.

GOAL: This paper presents a methodology for the automatic detection of sleep apnea from single-lead ...

Semisupervised ECG Ventricular Beat Classification With Novelty Detection Based on Switching Kalman Filters.

Automatic processing and accurate diagnosis of pathological electrocardiogram (ECG) signals remains ...

Phase information of time-frequency transforms as a key feature for classification of atrial fibrillation episodes.

Patients suffering from atrial fibrillation can be classified into different subtypes, according to ...

Robotic-assisted thermal ablation of liver tumours.

OBJECTIVE: This study aimed to assess the technical success, radiation dose, safety and performance ...

An ontology-based annotation of cardiac implantable electronic devices to detect therapy changes in a national registry.

The patient population benefitting from cardiac implantable electronic devices (CIEDs) is increasing...

Enhanced precision of tensor electrocardiography through increased cumulative distribution function resolution: Validation in healthy individuals

Deep-learning ECG analysis is advancing rapidly but lacks stable, physiologically interpretable indi...

Conformal Prediction and Ensemble Learning for Uncertainty-Aware ICU Mortality Stratification

Background. Conventional ICU severity scores - SOFA, qSOFA, and APACHE-II - use additive integer wei...

Deep learning optimisation for cardiology: Neural Architecture Search-driven arrhythmia classification with electrocardiograms

Cardiovascular disease is the leading cause of death worldwide. Sudden cardiac death (SCD) accounts ...

An ECG foundation model for generalizable cardiac function prediction across the lifespan

Background Artificial intelligence-enhanced electrocardiography (AI-ECG) enables scalable, low-cost ...

A Signal-Language Foundation Model for Broad-Spectrum Cardiovascular Assessment from Routine Electrocardiography

Electrocardiography (ECG) is central to cardiovascular care, but conventional AI models are often re...

TriDP-PTM: a three-stage distortion-perception tradeoff guides the pre-training model for radar cardiac sensing

Cardiovascular diseases (CVDs) remain a leading cause of death globally, necessitating continuous, a...

Biomarker Signal Architecture in Cardiovascular Machine Learning: Stability, Redundancy, and Minimal High-Yield Panels After Myocardial Infarction

Background: Machine-learning models based on circulating biomarkers are increasingly used in cardiov...