Analysis on risk factors and characteristics of coronary angiography in young men with CHD [PDF]
Journal of Men's Health, 2023 To examine the risk factors associated with coronary heart disease (CHD) in young males and assess the distinctive features of coronary angiography (CAG).
Xuhang Hua, Bo Chen, Yongchao Dong
doaj +1 more source
ON THE ELECTROCARDIOGRAM [PDF]
Quarterly Journal of Experimental Physiology, 1915 n ...
openaire +2 more sources
T-wave Inversion through Inhomogeneous Voltage Diffusion within the FK3V Cardiac Model [PDF]
Chaos 34, 043140 (2024), 2023 The heart beats due to the synchronized contraction of cardiomyocytes triggered by a periodic sequence of electrical signals called action potentials, which originate in the sinoatrial node and spread through the heart's electrical system. A large body of work is devoted to modeling the propagation of the action potential and to reproducing reliably ...
arxiv +1 more source
A Multimodel Fusion Method for Cardiovascular Disease Detection Using ECG
Emergency Medicine International, 2022 Objective. Electrocardiogram (ECG) is an important diagnostic tool that has been the subject of much research in recent years. Owing to a lack of well-labeled ECG record databases, most of this work has focused on heartbeat arrhythmia detection based on ...
Guanghui Song +4 more
doaj +1 more source
A Novel Heart Disease Classification Algorithm based on Fourier Transform and Persistent Homology [PDF]
arXiv, 2021 Classification and prediction of heart disease is a significant problem to realize medical treatment and life protection. In this paper, persistent homology is involved to analyze electrocardiograms and a novel heart disease classification method is proposed.
arxiv
Mathematical Model with Autoregressive Process for Electrocardiogram Signals [PDF]
Communications in Nonlinear Science and Numerical Simulation,
Volume 57, Pages 415-421, 2018, 2017 The cardiovascular system is composed of the heart, blood and blood vessels. Regarding the heart, cardiac conditions are determined by the electrocardiogram, that is a noninvasive medical procedure. In this work, we propose autoregressive process in a mathematical model based on coupled differential equations in order to model electrocardiogram signals.
arxiv +1 more source
Training neural networks with synthetic electrocardiograms [PDF]
arXiv, 2021 We present a method for training neural networks with synthetic electrocardiograms that mimic signals produced by a wearable single lead electrocardiogram monitor. We use domain randomization where the synthetic signal properties such as the waveform shape, RR-intervals and noise are varied for every training example. Models trained with synthetic data
arxiv
Lead-agnostic Self-supervised Learning for Local and Global Representations of Electrocardiogram [PDF]
arXiv, 2022 In recent years, self-supervised learning methods have shown significant improvement for pre-training with unlabeled data and have proven helpful for electrocardiogram signals. However, most previous pre-training methods for electrocardiogram focused on capturing only global contextual representations.
arxiv
Fully Automatic Electrocardiogram Classification System based on Generative Adversarial Network with Auxiliary Classifier [PDF]
Expert Systems with Applications, Volume 174, 2021, 114809, ISSN
0957-4174, 2020 A generative adversarial network (GAN) based fully automatic electrocardiogram (ECG) arrhythmia classification system with high performance is presented in this paper. The generator (G) in our GAN is designed to generate various coupling matrix inputs conditioned on different arrhythmia classes for data augmentation.
arxiv +1 more source
Accuracy Improvement for Fully Convolutional Networks via Selective Augmentation with Applications to Electrocardiogram Data [PDF]
, 2021 Deep learning methods have shown suitability for time series classification in the health and medical domain, with promising results for electrocardiogram data classification. Successful identification of myocardial infarction holds life saving potential and any meaningful improvement upon deep learning models in this area is of great interest ...
arxiv +1 more source