Latest AI and machine learning research in arrhythmias for healthcare professionals.
BACKGROUND: Shock-refractory ventricular fibrillation (VF) patients can be defined as those requirin...
Atrial fibrillation (AF) remains a leading driver of stroke and heart failure, yet timely diagnosis ...
OBJECTIVES: This study, from an interdisciplinary perspective of human factors engineering and biome...
OBJECTIVE: Identifying heart failure (HF) from electrocardiograms (ECG) is challenging due to the la...
Video-based or image-based human activity recognition (HAR) via machine learning algorithms helps tr...
Pneumonia remains a leading cause of in-hospital mortality worldwide. Current prognostic tools such ...
OBJECTIVE: Irreversible electroporation (IRE) represents a promising non-thermal ablation modality f...
AIMS: Electrocardiogram (ECG) recordings are fundamental for diagnosing cardiac conditions. Recent a...
Proper diagnosis of crop diseases and accurate measurement of fruit ripeness is essential in enhanci...
BACKGROUND: The identification of reliable biomarkers for atrial fibrillation (AF) recurrence post-c...
BACKGROUND: Left ventricular filling pressure is associated with heart failure symptoms and a key pr...
An ECG-based artificial intelligence (AI) model was previously developed to generate ten digital bio...
Machine learning struggles with imbalanced data. Although several mitigation approaches exist, their...
The analysis of Electrocardiogram (ECG) signals is critical for clinical applications, but current m...
Electrocardiogram (ECG) has been widely used in the diagnosis of cardiovascular disease (CVD). Curre...
BACKGROUND: Artificial intelligence-enhanced electrocardiography (AI-ECG) for detecting atrial fibri...
BACKGROUND: Peak oxygen consumption (peak VO2), the gold standard measure of cardiorespiratory fitne...
BACKGROUND: Artificial intelligence-augmented electrocardiogram (AI-ECG) models for detecting left v...
BACKGROUND: Atrial fibrillation (AF) and atrial flutter (AFL) are common arrhythmias associated with...
Deep learning models for biomedical signal analysis achieve high accuracy but suffer from interpreta...
\textit{Objective.} Motion artifacts remain a major obstacle in dynamic computed tomography (CT) rec...