Cardiovascular

Arrhythmias

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

2,496 articles
Stay Ahead - Weekly Arrhythmias research updates
Subscribe
Browse Categories
Showing 1744-1764 of 2,496 articles
Learning geometry-dependent lead-field operators for forward ECG modeling

Modern forward electrocardiogram (ECG) computational models rely on an accurate representation of th...

AI-Detected Asymptomatic Atrial Fibrillation and Risk of Incident Ischemic Stroke and Cardiovascular Events: A UK Biobank Study

Background: Advances in wearable devices and machine-learning-based ECG analysis enable highly accur...

Position: Evaluation of ECG Representations Must Be Fixed

This position paper argues that current benchmarking practice in 12-lead ECG representation learning...

Wavelet-Domain Multi-Representation and Ensemble Learning for Automated ECG Analysis

Accurate diagnosis of cardiac abnormalities from electrocardiogram signals remains a central challen...

CAMEL: An ECG Language Model for Forecasting Cardiac Events

Electrocardiograms (ECG) are electrical recordings of the heart that are critical for diagnosing car...

Prediction of Left Atrial Volume Parameters from Resting ECGs and Tabular Data Using Deep Learning in the UK Biobank

We present a deep learning model that predicts left atrial (LA) volume from standard 12-lead ECG rec...

Dual-Phase Cross-Modal Contrastive Learning for CMR-Guided ECG Representations for Cardiovascular Disease Assessment

Cardiac magnetic resonance imaging (CMR) offers detailed evaluation of cardiac structure and functio...

Contrastive Learning for Multi Label ECG Classification with Jaccard Score Based Sigmoid Loss

Recent advances in large language models (LLMs) have enabled the development of multimodal medical A...

ECG-IMN: Interpretable Mesomorphic Neural Networks for 12-Lead Electrocardiogram Interpretation

Deep learning has achieved expert-level performance in automated electrocardiogram (ECG) diagnosis, ...

Leveraging the wearable 1-lead ECG signal: From cardiac rhythm to cardiac function assessment

The electrocardiogram (ECG) is a critical tool in the diagnosis and monitoring of cardiovascular dis...

Prenatal Stress Detection from Electrocardiography Using Self-Supervised Deep Learning: Development and External Validation

Prenatal psychological stress affects 15-25% of pregnancies and increases risks of preterm birth, lo...

AI-Enabled Privacy-Preserving Cardiac Diagnostics via Electrocardiograms

Electrocardiogram (ECG) is a widely available, non-invasive diagnostic tool used for cardiovascular ...

UniPACT: A Multimodal Framework for Prognostic Question Answering on Raw ECG and Structured EHR

Accurate clinical prognosis requires synthesizing structured Electronic Health Records (EHRs) with r...

Development and Multinational Validation of Artificial Intelligence-Enabled ASCVD Risk Stratification Using Electrocardiograms

Aims: Despite the availability of clinical risk scores for atherosclerotic cardiovascular disease (A...

Deep Learning Decodes Latent ECG Signatures of Stress Cardiomyopathy

Background Stress cardiomyopathy (SCM) shares features with acute myocardial infarction (AMI) which ...

Time-series ECG Imputation Using a Pattern-Based Masking Framework

The utilization of continuous ECG monitoring has become an integral part of modern hospital-based ca...

Robust and Generalizable Atrial Fibrillation Detection from ECG Using Time-Frequency Fusion and Supervised Contrastive Learning

Atrial fibrillation (AF) is a common cardiac arrhythmia that significantly increases the risk of str...

Deep learning enables diagnosis of atrial cardiomyopathy from routine 12-lead electrocardiogram

BackgroundAtrial cardiomyopathy (AtCM) is both a cause and a consequence of atrial fibrillation and ...

Detection of Intelligent Tampering in Wireless Electrocardiogram Signals Using Hybrid Machine Learning

With the proliferation of wireless electrocardiogram (ECG) systems for health monitoring and authe...

Browse Categories