Latest AI and machine learning research in arrhythmias for healthcare professionals.
BACKGROUND: Artificial intelligence (AI)-enabled electrocardiography (ECG) can be used to predict ri...
This study presented a novel approach for the precise ablation of breast tumors using focused ultras...
The electrocardiogram (ECG) is a fundamental and widely used tool for diagnosing cardiovascular dise...
Purpose To develop and evaluate a publicly available deep learning model for segmenting and classify...
BACKGROUND: Several ablation confirmation software methods for minimum ablative margin assessment ha...
BACKGROUND: Artificial intelligence-enhanced electrocardiogram (AI-ECG) analysis shows promise to de...
Atrial fibrillation (AF) is a life-threatening heart condition, and its early detection and treatmen...
Sudden cardiac arrest (SCA) is a lethal cardiac arrhythmia that poses a serious threat to human life...
Electrocardiogram (ECG) is one of the reference cardiovascular diagnostic exams. However, the ECG si...
Feature attribution methods stand as a popular approach for explaining the decisions made by convolu...
Developing novel predictive models with complex biomedical information is challenging due to various...
Atrial fibrillation (AF) prediction and screening are of important clinical interest because of the ...
Robotic catheters enable precise steering of their distal tip while inside the body's blood vessels,...
Reducing electrophysiological (EP) signal noise is essential for diagnosis, mapping, and ablation, y...
Wearable cardiac monitors can be used to detect potential heart attack by syncing with smartphone ap...
The classification algorithms of rhythm and morphology abnormalities in electrocardiogram (ECG) sign...
Common artefacts such as baseline drift, rescaling, and noise critically limit the performance of ma...
While pre-trained neural networks, e.g., for diagnosis from electrocardiograms (ECGs), are already a...
Atrial Fibrillation (AFib) represents a prevalent cardiac arrhythmia associated with substantial ris...
This paper presents an innovative approach to recognizing personality traits using deep learning (DL...
This paper presents a novel approach to noninvasive hyperglycemia monitoring utilizing electrocardio...