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Atrial Fibrillation (AF) is a heart's arrhythmia which, despite being often asymptomatic, represents an important risk factor for stroke, therefore being able to predict AF at the electrocardiogram exam, would be of great impact on actively…

Signal Processing · Electrical Eng. & Systems 2022-02-14 A. Scagnetto , G. Barbati , I. Gandin , C. Cappelletto , G. Baj , A. Cazzaniga , F. Cuturello , A. Ansuini , L. Bortolussi , A. Di Lenarda

Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia worldwide, with 2% of the population affected. It is associated with an increased risk of strokes, heart failure and other heart-related complications. Monitoring at-risk…

Machine Learning · Computer Science 2021-11-24 Sideshwar J B , Sachin Krishan T , Vishal Nagarajan , Shanthakumar S , Vineeth Vijayaraghavan

Atrial fibrillation (AF) is the most common arrhythmia, increasing the risk of stroke, heart failure, and other cardiovascular complications. While AF detection algorithms perform well in identifying persistent AF, early-stage progression,…

Machine Learning · Computer Science 2025-08-28 Yongbin Lee , Ki H. Chon

Objectives: Atrial fibrillation (AF) is a common heart rhythm disorder associated with deadly and debilitating consequences including heart failure, stroke, poor mental health, reduced quality of life and death. Having an automatic system…

Signal Processing · Electrical Eng. & Systems 2018-01-31 Philip Warrick , Masun Nabhan Homsi

Atrial fibrillation (AF) is the most common cardiac arrhythmia, which is clinically identified with irregular and rapid heartbeat rhythm. AF puts a patient at risk of forming blood clots, which can eventually lead to heart failure, stroke,…

Signal Processing · Electrical Eng. & Systems 2023-06-28 Jianxin Xie , Stavros Stavrakis , Bing Yao

Atrial fibrillation (AF) is a common cardiac arrhythmia and a major risk factor for ischemic stroke. Early detection of AF using non-invasive signals can enable timely intervention. In this work, we present a comprehensive machine learning…

Computers and Society · Computer Science 2026-02-23 Ankit Singh , Vidhi Thakur , Nachiket Tapas

Atrial fibrillation is a cardiac arrhythmia that affects an estimated 33.5 million people globally and is the potential cause of 1 in 3 strokes in people over the age of 60. Detection and diagnosis of atrial fibrillation (AFIB) is done…

Machine Learning · Computer Science 2019-03-29 Sara Ross-Howe , H. R. Tizhoosh

Atrial Fibrillation (AF) is the most common type of arrhythmia (Greek a-, loss + rhythmos, rhythm = loss of rhythm) leading to hospitalization in the United States. Though sometimes AF is asymptomatic, it increases the risk of stroke and…

Machine Learning · Computer Science 2021-09-22 Samayan Bhattacharya , Sk Shahnawaz

A network-based approach is presented to investigate the cerebrovascular flow patterns during atrial fibrillation (AF) with respect to normal sinus rhythm (NSR). AF, the most common cardiac arrhythmia with faster and irregular beating, has…

Data Analysis, Statistics and Probability · Physics 2017-09-27 Stefania Scarsoglio , Fabio Cazzato , Luca Ridolfi

Atrial Fibrillation (AF) is among one of the most common types of heart arrhythmia afflicting more than 3 million people in the U.S. alone. AF is estimated to be the cause of death of 1 in 4 individuals. Recent advancements in Artificial…

Signal Processing · Electrical Eng. & Systems 2020-11-03 James Belen , Sajad Mousavi , Alireza Shamsoshoara , Fatemeh Afghah

Atrial fibrillation (AF) is the most common cardiac arrhythmia in human beings, and is associated with significant morbidity and mortality. The current standard of care includes interventional catheter ablation in selected patients, but the…

Atrial fibrillation (AF) is a common cardiac arrhythmia that significantly increases the risk of stroke and heart failure, necessitating reliable and generalizable detection methods from electrocardiogram (ECG) recordings. Although deep…

Quantitative Methods · Quantitative Biology 2026-01-16 Hongtao Li , Jia Wei , Jia Xiao , Yuanjun Lai , Mingyang Liu , Shuzhen Lv , Xueqiang Ouyang

Atrial fibrillation (AF) is the most common cardiac arrhythmia and associated with a high risk for serious conditions like stroke. The use of wearable devices embedded with automatic and timely AF assessment from electrocardiograms (ECGs)…

Signal Processing · Electrical Eng. & Systems 2023-09-12 Leonie Basso , Zhao Ren , Wolfgang Nejdl

Atrial fibrillation (AF) is the most common abnormal heart rhythm and the single biggest cause of stroke. Ablation, destroying regions of the atria, is applied largely empirically and can be curative but with a disappointing clinical…

Medical Physics · Physics 2015-06-19 Kim Christensen , Kishan A. Manani , Nicholas S. Peters

We develop a deep learning model, ABioSPATH, to predict the one-year risk of ischemic stroke (IS) in atrial fibrillation (AF) patients. The model integrates drug-protein-disease pathways and real-world clinical data of AF patients to…

Quantitative Methods · Quantitative Biology 2024-08-27 Zhiheng Lyu , Jiannan Yang , Zhongzhi Xu , Weilan Wang , Weibin Cheng , Kwok-Leung Tsui , Gary Tse , Qingpeng Zhang

Except for a few specific types, cardiac arrhythmias are not immediately life-threatening. However, if not treated appropriately, they can cause serious complications. In particular, atrial fibrillation, which is characterized by fast and…

Machine Learning · Computer Science 2020-10-08 Jérôme Van Zaen , Ricard Delgado-Gonzalo , Damien Ferrario Mathieu Lemay

Background: Atrial fibrillation (AF) is one of the most common cardiac arrhythmias that affects millions of people each year worldwide and it is closely linked to increased risk of cardiovascular diseases such as stroke and heart failure.…

Hypertrophic cardiomyopathy (HCM) patients have a high incidence of atrial fibrillation (AF) and increased stroke risk, even with low risk of congestive heart failure, hypertension, age, diabetes, previous stroke/transient ischemic attack…

Atrial fibrillation (AF) is one of the most prevalent cardiac arrhythmias that affects the lives of more than 3 million people in the U.S. and over 33 million people around the world and is associated with a five-fold increased risk of…

Quantitative Methods · Quantitative Biology 2020-02-14 Sajad Mousavi , Fatemeh Afghah , U. Rajendra Acharya

It is challenging to visually detect heart disease from the electrocardiographic (ECG) signals. Implementing an automated ECG signal detection system can help diagnosis arrhythmia in order to improve the accuracy of diagnosis. In this…

Signal Processing · Electrical Eng. & Systems 2020-11-13 Jiacheng Wang , Weiheng Li
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