Latest AI and machine learning research in arrhythmias for healthcare professionals.
Early structural heart disease (SHD) detection is crucial for improving prognostic outcomes, but wid...
Timely and accurate assessment of electrocardiograms (ECGs) is crucial for diagnosing, triaging, and...
Hypertrophic cardiomyopathy (HCM) is frequently underdiagnosed. While deep learning (DL) models usin...
The role of electrocardiography (ECG) has been limited in the preoperative risk evaluation in noncar...
Fluoroquinolones, while clinically indispensable, carry underappreciated cardiovascular risks, parti...
This study aims to present the Segmentation-based Myocardial Advanced Refinement Tracking (SMART) sy...
Assessing the risk of future atherosclerotic cardiovascular disease (ASCVD) is crucial in clinical p...
Off-label drug use, i.e., uses of a drug that differ from what regulatory authorities have approved,...
Atrial fibrillation (AF), a common cardiac arrhythmia, can lead to severe complications, emphasizing...
Artificial intelligence (AI) models can now detect patterns of structural heart diseases (SHDs) from...
The miniECG, a smartphone-sized, multi-lead device, offers a simple and fast alternative to the 12-l...
To evaluate the performance of an ensemble classifier, MultiECGNet, using multi-format electrocardio...
An electrocardiogram (ECG) is essential for diagnosing cardiac abnormalities. Automated heartbeat cl...
Although artificial intelligence–enhanced electrocardiography (AI-ECG) has shown promise in detectin...
Determination of cardiac output (CO) is essential to the clinical management of cardiovascular compr...
Synthetic data can be the solution to privacy requirements, can enrich datasets limited by underrepr...
Deep learning models have shown remarkable performance in electrocardiogram (ECG) analysis, but the ...
Artificial intelligence (AI)-enhanced electrocardiogram (ECG) models are designed to detect specific...
Electrocardiogram (ECG) analysis plays a critical role in the early detection and diagnosis of cardi...
In an analysis of 69,173 UK Biobank participants, we paired MRI-based measurements of the ascending ...
Machine learning models for predicting structural heart disease (SHD) from electrocardiography (ECG)...