Latest AI and machine learning research in arrhythmias for healthcare professionals.
BACKGROUND: Early diagnosis of acute coronary syndromes (ACS) remains challenging because electrical...
Stable angina pectoris is a prevalent condition with concerning symptoms and an increased risk of my...
Driven by rapid advancements in computational power and algorithmic innovations, artificial intellig...
Fetal arrhythmia is a critical medical condition associated with perinatal morbidity and cardiac com...
BACKGROUND: Diastolic dysfunction is common in patients with aortic stenosis and may influence outco...
AIMS: Pre-participation cardiovascular screening (PPS) is essential for preventing SCD in athletes, ...
Early identification of acute myocardial infarction (AMI) remains challenging, particularly in non-S...
IMPORTANCE: Transthyretin amyloid cardiomyopathy (ATTR-CM) is a treatable cause of heart failure, bu...
Multimodal physiological signal fusion-particularly electroencephalography (EEG) and electrocardiogr...
AIMS: We aimed to develop and validate echocardiography-based prediction models for light chain (AL)...
Seizure prediction is critically important, as it can help prevent serious injuries, improve quality...
OBJECTIVE: To develop and validate a radiomics-clinical model for individualized prediction of the i...
INTRODUCTION: Artificial intelligence electrocardiogram (AI-ECG) interpretation has emerged as a pro...
BACKGROUND: Intracardiac echocardiography (ICE) facilitates left atrial (LA) reconstruction during a...
BACKGROUND: Recent advances in deep learning have led to the development of ECG foundation models (E...
BACKGROUND: Artificial intelligence-enhanced electrocardiography (AI-ECG) may support ECG interpreta...
BACKGROUND: The growing integration of personalized risk prediction (PRP) and AI substantially resha...
Permanent pacemaker (PPM) implantation has been reported in up to 26% of patients undergoing transca...
Cardiovascular diseases remain a major global health burden, making accurate elec-trocardiogram (ECG...
OBJECTIVE: To propose a deep multimodal synergistic survival analysis framework (Deep Multimodal Syn...
Electrocardiogram (ECG) recordings are frequently corrupted by nonstationary artifacts such as basel...