Arrhythmias

A review on multimodal machine learning in medical diagnostics.

Nowadays, the increasing number of medical diagnostic data and clinical data provide more complement...

Non-contact wearable synchronous measurement method of electrocardiogram and seismocardiogram signals.

Cardiovascular disease is one of the leading threats to human lives and its fatality rate still rise...

[Artificial intelligence applied to the electrocardiogram, or is there really a needle in a haystack?].

Artificial intelligence applied to the standard Ecg (Ai-Ecg) is able to enormously enhance the perfo...

[Why artificial intelligence applied to the electrocardiogram is not yet clinical routine?].

Artificial intelligence opens up multiple application scenarios to the electrocardiogram (Ai-Ecg) in...

[Fetal electrocardiogram signal extraction and analysis method combining fast independent component analysis algorithm and convolutional neural network].

Fetal electrocardiogram (ECG) signals provide important clinical information for early diagnosis and...

Explainable AI for ECG-based prediction of cardiac resynchronization therapy outcomes: learning from machine learning?

Electrocardiogram-based deep learning improves outcome prediction following cardiac resynchronization therapy.

AIMS: This study aims to identify and visualize electrocardiogram (ECG) features using an explainabl...

Non-invasive localization of post-infarct ventricular tachycardia exit sites to guide ablation planning: a computational deep learning platform utilizing the 12-lead electrocardiogram and intracardiac electrograms from implanted devices.

AIMS: Existing strategies that identify post-infarct ventricular tachycardia (VT) ablation target ei...

A novel method for conformity assessment testing of defibrillators for post-market surveillance purposes.

BACKGROUND: Defibrillators are medical devices (MDs) used in the most critical situations, hence the...

A novel method for conformity assessment testing of electrocardiographs for post-market surveillance purposes.

BACKGROUND: Monitoring cardiac parameters is the fundamental aspect of every diagnostic process and ...

Automatic arrhythmia detection with multi-lead ECG signals based on heterogeneous graph attention networks.

Automatic arrhythmia detection is very important for cardiovascular health. It is generally performe...

A Deep Learning Scheme for Detecting Atrial Fibrillation Based on Fusion of Raw and Discrete Wavelet Transformed ECG Features.

Atrial fibrillation is the most common sustained cardiac arrhythmia and the electrocardiogram (ECG) ...

A U - Net Deep Learning Model for Infant Heart Rate Estimation from Ballistography.

Ballistography(BSG) is a non-intrusive and low- cost alternative to electrocardiography (ECG) for he...

Improving Deep Learning-based Cardiac Abnormality Detection in 12-Lead ECG with Data Augmentation.

Automated Electrocardiogram (ECG) classification using deep neural networks requires large datasets ...

Normal and Abnormal Classification of Electrocardiogram: A Primary Screening Tool Kit.

Cardiovascular diseases (CVDs) are one of the principal causes of death. Cardiac arrhythmia, a criti...

LTH-ECG: Lottery Ticket Hypothesis-based Deep Learning Model Compression for Atrial Fibrillation Detection from Single Lead ECG On Wearable and Implantable Devices.

Atrial Fibrillation (AF) is a kind of arrhythmia, which is a major morbidity factor, and AF can lead...

[Electrocardiogram signal classification algorithm of nested long short-term memory network based on focal loss function].

Electrocardiogram (ECG) can visually reflect the physiological electrical activity of human heart, w...

[Automatic detection model of hypertrophic cardiomyopathy based on deep convolutional neural network].

The diagnosis of hypertrophic cardiomyopathy (HCM) is of great significance for the early risk class...

Fighting against sudden cardiac death: need for a paradigm shift-Adding near-term prevention and pre-emptive action to long-term prevention.

More than 40 years after the first implantable cardioverter-defibrillator (ICD) implantation, sudden...

TF-Unet:An automatic cardiac MRI image segmentation method.

Personalized heart models are widely used to study the mechanisms of cardiac arrhythmias and have be...

Development of the AI-Cirrhosis-ECG Score: An Electrocardiogram-Based Deep Learning Model in Cirrhosis.

INTRODUCTION: Cirrhosis is associated with cardiac dysfunction and distinct electrocardiogram (ECG) ...