Latest AI and machine learning research in arrhythmias for healthcare professionals.
PPG-to-vital-sign reconstruction turns a wrist-worn photoplethysmogram into clinical waveforms such ...
Electrocardiography (ECG) contains subject-specific morphology that supports biometric recognition, ...
Background: Cascade screening increasingly identifies carriers of pathogenic or likely pathogenic sa...
Deep learning has advanced automated electrocardiogram (ECG) diagnosis, but the field's most accurat...
Conventional bibliometrics rely on lifetime citations, obscuring immediate shifts in cardiovascular ...
Objective: We developed a data-efficient deep learning framework for three-dimensional segmentation ...
Ultrasound is the most widely deployed imaging modality worldwide, yet clinical AI remains fragmente...
Chagas disease is a major cause of cardiomyopathy in Latin America. Cardiac magnetic resonance (CMR)...
False ventricular tachycardia (VT) alarms are a leading contributor to alarm fatigue in intensive ca...
Atrial fibrillation (AF) is the most common cardiac arrhythmia and is associated with increased risk...
Late Gadolinium Enhancement (LGE) on cardiac magnetic resonance is a key marker of myocardial scar, ...
Multimodal biomarkers have transformed Alzheimer's disease research, but the incremental contributio...
Artificial intelligence applied to routine electrocardiograms (ECGs) has largely focused on detectin...
Vision-language models (VLMs) can comply with harmful requests delivered through images, even when t...
Patient-conditioned acquisition policies for ECG lead-channel selection can outperform population-wi...
12-lead electrocardiogram (ECG) is a standard, non-invasive examination widely used for diagnosing c...
Wearable electrocardiogram (ECG) and photoplethysmogram (PPG) sensors are complementary but individu...
Self-repairs, in-utterance revisions in which a speaker abandons and reformulates their speech, are ...
Reproducibility of heart rate variability (HRV) analysis is limited by differences in preprocessing ...
Deep learning models for electrocardiogram (ECG) classification often suffer from significant perfor...
LGE cardiac MRI is widely used for left atrial fibrosis assessment and ablation planning in atrial f...