Arrhythmias

Ensembling convolutional and long short-term memory networks for electrocardiogram arrhythmia detection.

OBJECTIVE: Atrial fibrillation is a common type of heart rhythm abnormality caused by a problem with...

A convolutional neural network for ECG annotation as the basis for classification of cardiac rhythms.

OBJECTIVE: Electrocardiography is the most common tool to diagnose cardiovascular diseases. Annotati...

Rethinking multiscale cardiac electrophysiology with machine learning and predictive modelling.

We review some of the latest approaches to analysing cardiac electrophysiology data using machine le...

ECG Signal Classification Using Various Machine Learning Techniques.

Electrocardiogram (ECG) signal is a process that records the heart rate by using electrodes and dete...

ECG authentication system design incorporating a convolutional neural network and generalized S-Transformation.

Electrocardiogram (ECG) is gaining increased attention as a biometric method in a wide range of appl...

ECG signal classification for the detection of cardiac arrhythmias using a convolutional recurrent neural network.

OBJECTIVE: The electrocardiogram (ECG) provides an effective, non-invasive approach for clinical dia...

Towards End-to-End ECG Classification With Raw Signal Extraction and Deep Neural Networks.

This paper proposes deep learning methods with signal alignment that facilitate the end-to-end class...

Multi-stage SVM approach for cardiac arrhythmias detection in short single-lead ECG recorded by a wearable device.

OBJECTIVE: Use of wearable ECG devices for arrhythmia screening is limited due to poor signal qualit...

Parallel use of a convolutional neural network and bagged tree ensemble for the classification of Holter ECG.

UNLABELLED: The automated detection of arrhythmia in a Holter ECG signal is a challenging task due t...

Remote vs. conventional navigation for catheter ablation of atrial fibrillation: insights from prospective registry data.

BACKGROUND: Robotic (RNS) or magnetic navigation systems (MNS) are available for remotely performed ...

Predictors of atrial fibrillation early recurrence following cryoballoon ablation of pulmonary veins using statistical assessment and machine learning algorithms.

Inflammation, oxidative stress, myocardial injury biomarkers and clinical parameters (longer AF dura...

Analyzing single-lead short ECG recordings using dense convolutional neural networks and feature-based post-processing to detect atrial fibrillation.

OBJECTIVE: The prevalence of atrial fibrillation (AF) in the general population is 0.5%-1%. As AF is...

Temporal Performance of Laplacian Eigenmaps and 3D Conduction Velocity in Detecting Ischemic Stress.

BACKGROUND: Myocardial ischemia has a complex and time-varying electrocardiographic signature that i...

Densely connected convolutional networks for detection of atrial fibrillation from short single-lead ECG recordings.

The development of new technology such as wearables that record high-quality single channel ECG, pro...

Multiscaled Fusion of Deep Convolutional Neural Networks for Screening Atrial Fibrillation From Single Lead Short ECG Recordings.

Atrial fibrillation (AF) is one of the most common sustained chronic cardiac arrhythmia in elderly p...

Automatic recognition of arrhythmia based on principal component analysis network and linear support vector machine.

Electrocardiogram (ECG) classification is an important process in identifying arrhythmia, and neural...

Atrial Fibrillation Beat Identification Using the Combination of Modified Frequency Slice Wavelet Transform and Convolutional Neural Networks.

Atrial fibrillation (AF) is a serious cardiovascular disease with the phenomenon of beating irregula...

A support vector machine approach for AF classification from a short single-lead ECG recording.

OBJECTIVE: In this paper, a support vector machine (SVM) approach using statistical features, P wave...

Application of an optimal class of antisymmetric wavelet filter banks for obstructive sleep apnea diagnosis using ECG signals.

Obstructive sleep apnea (OSA) is a sleep disorder caused due to interruption of breathing resulting ...

A novel application of deep learning for single-lead ECG classification.

Detecting and classifying cardiac arrhythmias is critical to the diagnosis of patients with cardiac ...

Robotic magnetic catheter navigation as a first step in the automation of the ablation procedures for ventricular arrhythmia.