Computer-aided diagnosis of atrial fibrillation based on ECG Signals: A review
Arrhythmia is a type of disorder that affects the pattern and rate of the heartbeat. Among the
various arrhythmia conditions, atrial fibrillation (AF) is the most prevalent. AF is associated …
various arrhythmia conditions, atrial fibrillation (AF) is the most prevalent. AF is associated …
A review on the state of the art in atrial fibrillation detection enabled by machine learning
Atrial Fibrillation (AF) the most commonly occurring type of cardiac arrhythmia is one of the
main causes of morbidity and mortality worldwide. The timely diagnosis of AF is an equally …
main causes of morbidity and mortality worldwide. The timely diagnosis of AF is an equally …
HAN-ECG: An interpretable atrial fibrillation detection model using hierarchical attention networks
Atrial fibrillation (AF) is one of the most prevalent cardiac arrhythmias that affects the lives of
many people around the world and is associated with a five-fold increased risk of stroke and …
many people around the world and is associated with a five-fold increased risk of stroke and …
Atrial fibrillation classification with smart wearables using short-term heart rate variability and deep convolutional neural networks
Atrial fibrillation (AF) is a type of cardiac arrhythmia affecting millions of people every year.
This disease increases the likelihood of strokes, heart failure, and even death. While …
This disease increases the likelihood of strokes, heart failure, and even death. While …
Machine learning detection of Atrial Fibrillation using wearable technology
Background Atrial Fibrillation is the most common arrhythmia worldwide with a global age
adjusted prevalence of 0.5% in 2010. Anticoagulation treatment using warfarin or direct oral …
adjusted prevalence of 0.5% in 2010. Anticoagulation treatment using warfarin or direct oral …
Atrial fibrillation detection using heart rate variability and atrial activity: A hybrid approach
G Hirsch, SH Jensen, ES Poulsen… - Expert Systems with …, 2021 - Elsevier
Goal: Develop a real-time hybrid scheme for the automatic detection of atrial fibrillation (AF),
based on the RR interval (RRI) time series and the atrial activity (AA) derived from the …
based on the RR interval (RRI) time series and the atrial activity (AA) derived from the …
MGNN: A multiscale grouped convolutional neural network for efficient atrial fibrillation detection
S Liu, A Wang, X Deng, C Yang - Computers in Biology and Medicine, 2022 - Elsevier
The reliable detection of atrial fibrillation (AF) is of great significance for monitoring disease
progression and developing tailored care paths. In this work, we proposed a novel and …
progression and developing tailored care paths. In this work, we proposed a novel and …
Detection of atrial fibrillation episodes in long-term heart rhythm signals using a support vector machine
Atrial fibrillation (AF) is a serious heart arrhythmia leading to a significant increase of the risk
for occurrence of ischemic stroke. Clinically, the AF episode is recognized in an …
for occurrence of ischemic stroke. Clinically, the AF episode is recognized in an …
Considerations on performance evaluation of atrial fibrillation detectors
Objective: A large number of atrial fibrillation (AF) detectors have been published in recent
years, signifying that the comparison of detector performance plays a central role, though not …
years, signifying that the comparison of detector performance plays a central role, though not …
Early detection of atrial fibrillation based on ECG signals
N Ahmed, Y Zhu - Bioengineering, 2020 - mdpi.com
Atrial fibrillation, often called AF is considered to be the most common type of cardiac
arrhythmia, which is a major healthcare challenge. Early detection of AF and the appropriate …
arrhythmia, which is a major healthcare challenge. Early detection of AF and the appropriate …