AIMC Topic: Atrial Fibrillation
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A novel XAI framework for explainable AI-ECG using generative counterfactual XAI (GCX).
Scientific reports
Jul 2, 2025
Generative Counterfactual Explainable Artificial Intelligence (XAI) offers a novel approach to understanding how AI models interpret electrocardiograms (ECGs). Traditional explanation methods focus on highlighting important ECG segments but often fai...
Machine-learning model for predicting left atrial thrombus in patients with paroxysmal atrial fibrillation.
BMC cardiovascular disorders
Jun 2, 2025
OBJECTIVE: Left atrial thrombus (LAT) poses a significant risk for stroke and other thromboembolic complication in patients with atrial fibrillation (AF). This study aimed to evaluate the incidence and predictors of LAT in patients with paroxysmal AF...
Evaluating performance of large language models for atrial fibrillation management using different prompting strategies and languages.
Scientific reports
May 30, 2025
This study evaluated large language models (LLMs) using 30 questions, each derived from a recommendation in the 2024 European Society of Cardiology (ESC) guidelines for atrial fibrillation (AF) management. These recommendations were stratified by cla...
MicroRNA signature predicts post operative atrial fibrillation after coronary artery bypass grafting.
Scientific reports
May 28, 2025
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 detection via contactless radio monitoring and knowledge transfer.
Nature communications
May 20, 2025
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...
Deep learning based automated left atrial segmentation and flow quantification of real time phase contrast MRI in patients with atrial fibrillation.
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...
Observer Variation
Automation
Blood Flow Velocity
Atrial Function, Left
Heart Atria
Heart Rate
Image Interpretation, Computer-Assisted
Aged
Magnetic Resonance Imaging, Cine
Humans
Male
Female
Middle Aged
Reproducibility of Results
Time Factors
Deep Learning
Magnetic Resonance Imaging
Predictive Value of Tests
Atrial Fibrillation
Development of an Artificial Intelligence-Enabled Electrocardiography to Detect 23 Cardiac Arrhythmias and Predict Cardiovascular Outcomes.
Journal of medical systems
Apr 22, 2025
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...
Assessment of the long RR intervals using convolutional neural networks in single-lead long-term Holter electrocardiogram recordings.
Scientific reports
Apr 7, 2025
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...
Integrating deep learning with ECG, heart rate variability and demographic data for improved detection of atrial fibrillation.
Open heart
Mar 31, 2025
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...
The impact of training image quality with a novel protocol on artificial intelligence-based LGE-MRI image segmentation for potential atrial fibrillation management.
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...
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