Application of deep learning techniques for heartbeats detection using ECG signals-analysis and review
Deep learning models have become a popular mode to classify electrocardiogram (ECG)
data. Investigators have used a variety of deep learning techniques for this application …
data. Investigators have used a variety of deep learning techniques for this application …
Data preprocessing for heart disease classification: A systematic literature review
H Benhar, A Idri, JL Fernández-Alemán - Computer Methods and Programs …, 2020 - Elsevier
Context Early detection of heart disease is an important challenge since 17.3 million people
yearly lose their lives due to heart diseases. Besides, any error in diagnosis of cardiac …
yearly lose their lives due to heart diseases. Besides, any error in diagnosis of cardiac …
Temporal convolutional autoencoder for unsupervised anomaly detection in time series
Learning temporal patterns in time series remains a challenging task up until today.
Particularly for anomaly detection in time series, it is essential to learn the underlying …
Particularly for anomaly detection in time series, it is essential to learn the underlying …
A multitier deep learning model for arrhythmia detection
An electrocardiograph (ECG) is employed as a primary tool for diagnosing cardiovascular
diseases (CVDs). ECG signals provide a framework to probe the underlying properties and …
diseases (CVDs). ECG signals provide a framework to probe the underlying properties and …
Myocardial infarction detection based on deep neural network on imbalanced data
Myocardial infarction (MI) is an acute interruption of blood flow to the heart, which causes the
heart to suffer from a deficiency of blood and ischemia, so the heart muscle is damaged, and …
heart to suffer from a deficiency of blood and ischemia, so the heart muscle is damaged, and …
Prediction of heart disease and classifiers' sensitivity analysis
KM Almustafa - BMC bioinformatics, 2020 - Springer
Background Heart disease (HD) is one of the most common diseases nowadays, and an
early diagnosis of such a disease is a crucial task for many health care providers to prevent …
early diagnosis of such a disease is a crucial task for many health care providers to prevent …
An automated Residual Exemplar Local Binary Pattern and iterative ReliefF based COVID-19 detection method using chest X-ray image
Coronavirus is normally transmitted from animal to person, but nowadays it is transmitted
from person to person by changing its form. Covid-19 appeared as a very dangerous virus …
from person to person by changing its form. Covid-19 appeared as a very dangerous virus …
Generalization of convolutional neural networks for ECG classification using generative adversarial networks
Electrocardiograms (ECGs) play a vital role in the clinical diagnosis of heart diseases. An
ECG record of the heart signal over time can be used to discover numerous arrhythmias. Our …
ECG record of the heart signal over time can be used to discover numerous arrhythmias. Our …
Automated accurate speech emotion recognition system using twine shuffle pattern and iterative neighborhood component analysis techniques
Speech emotion recognition is one of the challenging research issues in the knowledge-
based system and various methods have been recommended to reach high classification …
based system and various methods have been recommended to reach high classification …
Surface EMG signal classification using ternary pattern and discrete wavelet transform based feature extraction for hand movement recognition
Hands are two of the most crucial organs and they play major role for human activities.
Therefore, amputee people experience many difficulties in daily life. To overcome these …
Therefore, amputee people experience many difficulties in daily life. To overcome these …