Latest AI and machine learning research in arrhythmias for healthcare professionals.
Cardiac CT plays an important role in diagnosing heart diseases but is conventionally limited by its...
The performance and long-term health of athletes are significantly influenced by their cardiovascula...
In electrocardiography (ECG), measurement of QRS duration (QRSd) is crucial for diagnosing condition...
We propose a deep learning approach for beat-wise atrial fibrillation (AF) detection in electrocardi...
Cardiac arrhythmias are irregular heart rhythms that, if undetected, can lead to severe cardiovascul...
Coronary artery disease (CAD) is a major cause of mortality, especially among aging populations, mak...
BACKGROUND AND OBJECTIVE: The 12-lead electrocardiography (ECG) is a widely used diagnostic method i...
Secundum atrial septal defect (ASD2) detection is often delayed, with the potential for late diagnos...
Sleep apnea is a prevalent disorder affecting 10Â % of middle-aged individuals, yet it remains underd...
The automatic classification of medical time series signals, such as electroencephalogram (EEG) an...
OBJECTIVES: An image-based ECG dataset incorporating visual imperfections common to paper-based ECGs...
Atrial fibrillation (AF) is a prevalent cardiac arrhythmia associated with elevated health risks, ...
This review focuses on the computerized modeling of the electrophysiology of the human atria, emph...
Reconstructing ECG from PPG is a promising yet challenging task. While recent advancements in gene...
We introduce an open-source Python framework for generating synthetic ECG image datasets to advanc...
In the field of automatic Electrocardiogram (ECG) diagnosis, due to the relatively limited amount ...
Accurate ECG interpretation is vital, yet complex cardiac data and "black-box" AI models limit cli...
BACKGROUND: Structural remodeling of the left atrial appendage (LAA) is characteristic of atrial fib...
Recent advances have increasingly applied large language models (LLMs) to electrocardiogram (ECG) ...
Cardiac digital twins (CDT) are emerging as a potentially transformative tool in cardiology. A cri...
In this article we comment on the paper by Xu describing retrospective data on endoscopic treatment...