Early detection of atrial fibrillation (AFib) is crucial for altering its natural progression and complication profile. Traditional demographic and lifestyle factors often fail as predictors of AFib. This study investigated pre-operative, circulating...
Atrial fibrillation (AF) has been a prevalent and serious arrhythmia associated with increased morbidity and mortality worldwide. The Electrocardiogram (ECG) is considered as the golden standard for AF diagnosis. However, current ECG is primarily use...
The international journal of cardiovascular imaging
Apr 29, 2025
Real time 2D phase contrast (RTPC) MRI is useful for flow quantification in atrial fibrillation (AF) patients, but data analysis requires time-consuming anatomical contouring for many cardiac time frames. Our goal was to develop a convolutional neura...
Arrhythmias are common and can affect individuals with or without structural heart disease. Deep learning models (DLMs) have shown the ability to recognize arrhythmias using 12-lead electrocardiograms (ECGs). However, the limited types of arrhythmias...
Advancements in medical technology have extended long-term electrocardiogram (ECG) monitoring from the traditional 24 h to 7-14 days, significantly enriching ECG data. However, this poses unprecedented challenges for physicians in analyzing these ext...
BACKGROUND: Atrial fibrillation (AF) is a common but often undiagnosed condition, increasing the risk of stroke and heart failure. Early detection is crucial, yet traditional methods struggle with AF's transient nature. This study investigates how au...
Computer methods and programs in biomedicine
Mar 15, 2025
BACKGROUND: Atrial fibrillation (AF) is the most common cardiac arrhythmia, affecting up to 2 % of the population. Catheter ablation is a promising treatment for AF, particularly for paroxysmal AF patients, but it often has high recurrence rates. Dev...
BACKGROUND: Conversational artificial intelligence (AI) allows for engaging interactions, however, its acceptability, barriers, and enablers to support patients with atrial fibrillation (AF) are unknown.
Portable and wearable electrocardiogram (ECG) devices are increasingly utilized in healthcare for monitoring heart rhythms and detecting cardiac arrhythmias or other heart conditions. The integration of ECG signal visualization with AI-based abnormal...
Data fusion, involving the simultaneous integration of signals from multiple sensors, is an emerging field that facilitates more accurate inferences in instrumentation applications. This paper presents a novel fusion methodology for multi-sensor mult...
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