AIMC Topic: Ventricular Premature Complexes
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Machine Learning for Localization of Premature Ventricular Contraction Origins: A Review.
Pacing and clinical electrophysiology : PACE
Oct 20, 2024
Premature ventricular contraction (PVC) is one of the most common arrhythmias, originating from ectopic beats in the ventricles. Precision in localizing the origin of PVCs has long been a focal point in electrophysiology research. Machine learning (M...
A multi-module algorithm for heartbeat classification based on unsupervised learning and adaptive feature transfer.
Computers in biology and medicine
Jan 28, 2024
The scarcity of annotated data is a common issue in the realm of heartbeat classification based on deep learning. Transfer learning (TL) has emerged as an effective strategy for addressing this issue. However, current TL techniques in this realm over...
Deep learning-based regional ECG diagnosis platform.
Pacing and clinical electrophysiology : PACE
Nov 29, 2023
OBJECTIVE: To enable the intelligent diagnosis of a variety of common Electrocardiogram (ECG), we investigate the deep learning-based ECG diagnosis system.
Enhancing the performance of premature ventricular contraction detection in unseen datasets through deep learning with denoise and contrast attention module.
Computers in biology and medicine
Oct 4, 2023
Premature ventricular contraction (PVC) is a common and harmless cardiac arrhythmia that can be asymptomatic or cause palpitations and chest pain in rare instances. However, frequent PVCs can lead to more serious arrhythmias, such as atrial fibrillat...
A Novel ECG-Based Deep Learning Algorithm to Predict Cardiomyopathy in Patients With Premature Ventricular Complexes.
JACC. Clinical electrophysiology
Jul 19, 2023
BACKGROUND: Premature ventricular complexes (PVCs) are prevalent and, although often benign, they may lead to PVC-induced cardiomyopathy. We created a deep-learning algorithm to predict left ventricular ejection fraction (LVEF) reduction in patients ...
An Energy Efficient ECG Ventricular Ectopic Beat Classifier Using Binarized CNN for Edge AI Devices.
IEEE transactions on biomedical circuits and systems
May 19, 2022
Wearable Artificial Intelligence-of-Things (AIoT) requires edge devices to be resource and energy-efficient. In this paper, we design and implement an efficient binary convolutional neural network (bCNN) algorithm utilizing function-merging and block...
Development of a Visualization Deep Learning Model for Classifying Origins of Ventricular Arrhythmias.
Circulation journal : official journal of the Japanese Circulation Society
Apr 7, 2022
BACKGROUND: Several algorithms have been proposed for differentiating the right and left outflow tracts (RVOT/LVOT) arrhythmia origins from 12-lead electrocardiograms (ECGs); however, the procedure is complicated. A deep learning (DL) model, a form o...
Premature Ventricular Contraction Recognition Based on a Deep Learning Approach.
Journal of healthcare engineering
Mar 26, 2022
Electrocardiogram signal (ECG) is considered a significant biological signal employed to diagnose heart diseases. An ECG signal allows the demonstration of the cyclical contraction and relaxation of human heart muscles. This signal is a primary and n...
Robust PVC Identification by Fusing Expert System and Deep Learning.
Biosensors
Mar 22, 2022
Premature ventricular contraction (PVC) is one of the common ventricular arrhythmias, which may cause stroke or sudden cardiac death. Automatic long-term electrocardiogram (ECG) analysis algorithms could provide diagnosis suggestion and even early wa...
Automatic detection of arrhythmias from an ECG signal using an auto-encoder and SVM classifier.
Physical and engineering sciences in medicine
Mar 18, 2022
Millions of people around the world are affected by arrhythmias, which are abnormal activities of the functioning of the heart. Most arrhythmias are harmful to the heart and can suddenly become life-threatening. The electrocardiogram (ECG) is an impo...
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