Latest AI and machine learning research in arrhythmias for healthcare professionals.
An electrocardiogram (ECG) captures the heart's electrical signal to assess various heart conditio...
Atrial fibrillation (AF) prediction and screening are of important clinical interest because of the ...
Cardiac digital twins (CDTs) of human cardiac electrophysiology (EP) are digital replicas of patie...
Purpose: Federated training is often hindered by heterogeneous datasets due to divergent data stor...
Mechanistic interpretability work attempts to reverse engineer the learned algorithms present insi...
Major depressive disorder (MDD) is a chronic mental illness which affects people's well-being and is...
Recent artificial intelligence (AI) advancements in cardiovascular medicine offer potential enhancem...
Photoplethysmography (PPG)-based arrhythmia detection methods have gained attention with wearable te...
This study presents an approach to human activity recognition (HAR) using electrocardiogram (ECG) si...
This paper presents a novel approach for classifying electrocardiogram (ECG) signals in healthcare a...
We introduce a Gradient-weighted Class Activation Mapping (Grad-CAM) methodology to assess the perfo...
Accurate differentiation between Ventricular Tachycardia (VT) and Ventricular Fibrillation (VF) is e...
Electrocardiogram data provide a tremendous opportunity for the detection of various types of cardia...
In practical scenarios involving the measurement of surface electromyography (sEMG) in muscles, part...
Atrial fibrillation (AF) is a common cardiac disease that potentially leads to fatal conditions. Mac...
This paper presents a novel approach to noninvasive hyperglycemia monitoring utilizing electrocardio...
This paper presents an innovative approach to recognizing personality traits using deep learning (DL...
Atrial Fibrillation (AFib) represents a prevalent cardiac arrhythmia associated with substantial ris...
While pre-trained neural networks, e.g., for diagnosis from electrocardiograms (ECGs), are already a...
Common artefacts such as baseline drift, rescaling, and noise critically limit the performance of ma...
The classification algorithms of rhythm and morphology abnormalities in electrocardiogram (ECG) sign...