AIMC Topic: Arrhythmias, Cardiac

Clear Filters Showing 171 to 180 of 287 articles

Automatic Detection of Arrhythmia Based on Multi-Resolution Representation of ECG Signal.

Sensors (Basel, Switzerland) Mar 12, 2020
Automatic detection of arrhythmia is of great significance for early prevention and diagnosis of cardiovascular disease. Traditional feature engineering methods based on expert knowledge lack multidimensional and multi-view information abstraction an...
Signal Processing, Computer-Assisted Arrhythmias, Cardiac Humans Neural Networks, Computer Electrocardiography
View on PubMed DOI

Usefulness of Machine Learning-Based Detection and Classification of Cardiac Arrhythmias With 12-Lead Electrocardiograms.

The Canadian journal of cardiology Mar 5, 2020
BACKGROUND: Deep-learning algorithms to annotate electrocardiograms (ECGs) and classify different types of cardiac arrhythmias with the use of a single-lead ECG input data set have been developed. It remains to be determined whether these algorithms ...
Middle Aged Algorithms Internal Medicine Humans Electrocardiography Emergency Medicine Machine Learning Female Arrhythmias, Cardiac Male Cardiologists
View on PubMed DOI

Machine learning for predicting cardiac events: what does the future hold?

Expert review of cardiovascular therapy Feb 23, 2020
: With the increase in the number of patients with cardiovascular diseases, better risk-prediction models for cardiovascular events are needed. Statistical-based risk-prediction models for cardiovascular events (CVEs) are available, but they lack the...
Humans Models, Statistical Heart Failure Arrhythmias, Cardiac Machine Learning Forecasting Cardiovascular Diseases
View on PubMed DOI

Transfer Learning in ECG Classification from Human to Horse Using a Novel Parallel Neural Network Architecture.

Scientific reports Jan 13, 2020
Automatic or semi-automatic analysis of the equine electrocardiogram (eECG) is currently not possible because human or small animal ECG analysis software is unreliable due to a different ECG morphology in horses resulting from a different cardiac inn...
Heart Rate Horses Wavelet Analysis Software Algorithms Animals Electrocardiography Signal Processing, Computer-Assisted Arrhythmias, Cardiac Humans Neural Networks, Computer Machine Learning
View on PubMed DOI

Single-modal and multi-modal false arrhythmia alarm reduction using attention-based convolutional and recurrent neural networks.

PloS one Jan 10, 2020
This study proposes a deep learning model that effectively suppresses the false alarms in the intensive care units (ICUs) without ignoring the true alarms using single- and multi- modal biosignals. Most of the current work in the literature are eithe...
Humans Neural Networks, Computer Algorithms Supervised Machine Learning Arrhythmias, Cardiac False Positive Reactions Intensive Care Units Sensitivity and Specificity Monitoring, Physiologic Clinical Alarms
View on PubMed DOI

A 13.34 μW Event-Driven Patient-Specific ANN Cardiac Arrhythmia Classifier for Wearable ECG Sensors.

IEEE transactions on biomedical circuits and systems Nov 28, 2019
Artificial neural network (ANN) and its variants are favored algorithm in designing cardiac arrhythmia classifier (CAC) for its high accuracy. However, the implementation of ultralow power ANN-CAC is challenging due to the intensive computations. Mor...
Humans Equipment Design Signal Processing, Computer-Assisted Arrhythmias, Cardiac Neural Networks, Computer Wearable Electronic Devices Electrocardiography
View on PubMed DOI

Heartbeat classification using deep residual convolutional neural network from 2-lead electrocardiogram.

Journal of electrocardiology Nov 22, 2019
BACKGROUND: The electrocardiogram (ECG) has been widely used in the diagnosis of heart disease such as arrhythmia due to its simplicity and non-invasive nature. Arrhythmia can be classified into many types, including life-threatening and non-life-thr...
Neural Networks, Computer Algorithms Electrocardiography Arrhythmias, Cardiac Heart Rate Humans
View on PubMed DOI

Automatic detection of arrhythmia from imbalanced ECG database using CNN model with SMOTE.

Australasian physical & engineering sciences in medicine Nov 14, 2019
Timely prediction of cardiovascular diseases with the help of a computer-aided diagnosis system minimizes the mortality rate of cardiac disease patients. Cardiac arrhythmia detection is one of the most challenging tasks, because the variations of ele...
Heart Rate Automation Task Performance and Analysis Humans Neural Networks, Computer Databases, Factual Algorithms Electrocardiography Arrhythmias, Cardiac
View on PubMed DOI

A Cascaded Convolutional Neural Network for Assessing Signal Quality of Dynamic ECG.

Computational and mathematical methods in medicine Oct 20, 2019
Motion artifacts and myoelectrical noise are common issues complicating the collection and processing of dynamic electrocardiogram (ECG) signals. Recent signal quality studies have utilized a binary classification metric in which ECG samples are dete...
Motion Arrhythmias, Cardiac Heart Rate China Signal Processing, Computer-Assisted Electrocardiography, Ambulatory Adult Humans Algorithms Artifacts Male Reproducibility of Results Neural Networks, Computer Databases, Factual Signal-To-Noise Ratio Aged Middle Aged Female Aged, 80 and over
View on PubMed DOI

An Effective LSTM Recurrent Network to Detect Arrhythmia on Imbalanced ECG Dataset.

Journal of healthcare engineering Oct 13, 2019
To reduce the high mortality rate from cardiovascular disease (CVD), the electrocardiogram (ECG) beat plays a significant role in computer-aided arrhythmia diagnosis systems. However, the complex variations and imbalance of ECG beats make this a chal...
Arrhythmias, Cardiac Signal-To-Noise Ratio Neural Networks, Computer Deep Learning Humans Electrocardiography Databases, Factual Signal Processing, Computer-Assisted Diagnosis, Computer-Assisted
View on PubMed DOI
Popular Topics
Recent Journals