Latest AI and machine learning research in arrhythmias for healthcare professionals.
INTRODUCTION: Catheter ablation of persistent atrial fibrillation yields sub-optimal success rates p...
BACKGROUND: Undetected atrial fibrillation (AF) poses a significant risk of stroke and cardiovascula...
OBJECTIVES: To evaluate the effectiveness of an MRI radiomics stacking ensemble learning model, whic...
Electrocardiogram (ECG) signals contain complex and diverse features, serving as a crucial basis for...
BACKGROUND: Catheter ablation is a common treatment for atrial fibrillation (AF), but recurrence rat...
The automatic detection of arrhythmia is of primary importance due to the huge number of victims cau...
The Electrocardiogram (ECG) remains a fundamental tool in cardiac diagnostics, yet its interpretatio...
Artificial Intelligence (AI) has been proposed to improve workflow for coronary artery calcium scori...
BACKGROUND: Large language models (LLMs) such as Chat Generative Pre-trained Transformer (ChatGPT) e...
BACKGROUND: The recurrence rate of strokes associated with atrial fibrillation (AF) can be substanti...
Individuals with neuropsychiatric disorders experience both physical and mental difficulties, hinder...
To assess the feasibility of utilizing a large language model (LLM) in extracting clinically relevan...
BACKGROUND: Artificial intelligence (AI) has revolutionized numerous industries, enhancing efficienc...
This work presents an energy-efficient ECG processor designed for Cardiac Arrhythmia Classification....
Atrial fibrillation (AF) is a complex condition caused by various underlying pathophysiological diso...
BACKGROUND: Atrial Fibrillation (AF) is the most common form of arrhythmia in the world with a preva...
Myocardial infarction (MI) is a life-threatening medical condition that necessitates both timely and...
BACKGROUND: The 12-lead electrocardiogram (ECG) is an established modality for cardiovascular assess...
Detecting early stages of cardiovascular disease from short-duration Electrocardiogram (ECG) signals...
AIMS: Through a simple machine learning approach, we aimed to assess the risk of all-cause mortality...
PURPOSE: To predict survival and tumor recurrence following image-guided thermal ablation (IGTA) of ...