Arrhythmias

Arrhythmias

Latest AI and machine learning research in arrhythmias for healthcare professionals.

2,007 articles

Cardiology Subcategories: Acute Coronary Syndrome Arrhythmias Atherosclerosis Congestive Heart Failure Dyslipidemia Hypertension Metabolic Syndrome Myocardial Infarction PCI Peripheral Artery Disease Prevention Strokes Venous Thrombosis

Showing 1681-1701 of 2,007 articles

Emerging Concepts and Applied Machine Learning Research in Patients with Drug-Induced Repolarization Disorders.

The paper presents a review of current research to develop predictive models for automated detection...

Jun 2020 32570374

Forecasting a Crisis: Machine-Learning Models Predict Occurrence of Intraoperative Bradycardia Associated With Hypotension.

BACKGROUND: Predictive analytics systems may improve perioperative care by enhancing preparation for...

May 2020 32287127

Deep learning for comprehensive ECG annotation.

BACKGROUND: Increasing utilization of long-term outpatient ambulatory electrocardiographic (ECG) mon...

May 2020 32354454

[Detection of inferior myocardial infarction based on densely connected convolutional neural network].

Inferior myocardial infarction is an acute ischemic heart disease with high mortality, which is easy...

Feb 2020 32096388

Contribution of neural networks in the diagnosis and treatment of cardiac arrhythmia.

Arrhythmia is a dangerous disease in which the heart rhythm varies and it may be very fast or very s...

Jan 2020 33357360

The electrocardiogram endeavour: from the Holter single-lead recordings to multilead wearable devices supported by computational machine learning algorithms.

This review aims to provide a comprehensive recapitulation of the evolution in the field of cardiac ...

Jan 2020 31535151

[Heartbeat-based end-to-end classification of arrhythmias].

OBJECTIVE: We propose a heartbeat-based end-to-end classification of arrhythmias to improve the clas...

Sep 2019 31640959

Deep Learning Based Patient-Specific Classification of Arrhythmia on ECG signal.

The classification of the heartbeat type is an essential function in the automatical electrocardiogr...

Jul 2019 31946178

Deep Learning Approach for Highly Specific Atrial Fibrillation and Flutter Detection based on RR Intervals.

Atrial fibrillation (AF) and atrial flutter (AFL) represent atrial arrhythmias closely related to in...

Jul 2019 31946242

A Robust Machine Learning Architecture for a Reliable ECG Rhythm Analysis during CPR.

Chest compressions delivered during cardiopulmonary resuscitation (CPR) induce artifacts in the ECG ...

Jul 2019 31946270

A Deep Learning Method to Detect Atrial Fibrillation Based on Continuous Wavelet Transform.

Atrial fibrillation (AF) is one of the most common arrhythmias. The automatic AF detection is of gre...

Jul 2019 31946271

An Electrocardiogram Delineator via Deep Segmentation Network.

Electrocardiogram (ECG) delineation is a process to detect multiple characteristic points, which con...

Jul 2019 31946272

Convolutional Recurrent Neural Networks to Characterize the Circulation Component in the Thoracic Impedance during Out-of-Hospital Cardiac Arrest.

Pulse detection during out-of-hospital cardiac arrest remains challenging for both novel and expert ...

Jul 2019 31946274

Cardiovascular

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Emerging Concepts and Applied Machine Learning Research in Patients with Drug-Induced Repolarization Disorders.

Forecasting a Crisis: Machine-Learning Models Predict Occurrence of Intraoperative Bradycardia Associated With Hypotension.

Deep learning for comprehensive ECG annotation.

[Detection of inferior myocardial infarction based on densely connected convolutional neural network].

Contribution of neural networks in the diagnosis and treatment of cardiac arrhythmia.

The electrocardiogram endeavour: from the Holter single-lead recordings to multilead wearable devices supported by computational machine learning algorithms.

[Heartbeat-based end-to-end classification of arrhythmias].

Deep Learning Based Patient-Specific Classification of Arrhythmia on ECG signal.

Deep Learning Approach for Highly Specific Atrial Fibrillation and Flutter Detection based on RR Intervals.

A Robust Machine Learning Architecture for a Reliable ECG Rhythm Analysis during CPR.

A Deep Learning Method to Detect Atrial Fibrillation Based on Continuous Wavelet Transform.

An Electrocardiogram Delineator via Deep Segmentation Network.

Convolutional Recurrent Neural Networks to Characterize the Circulation Component in the Thoracic Impedance during Out-of-Hospital Cardiac Arrest.

Myocardial Infarction Detection Based on Multi-lead Ensemble Neural Network.

Phase-domain Deep Patient-ECG Image Learning for Zero-effort Smart Health Security.

ECG Biometric Recognition: Template-Free Approaches Based on Deep Learning.

The Feasibility of Arrhythmias Detection from A Capacitive ECG Measurement Using Convolutional Neural Network.

Cardiovascular disease diagnosis using cross-domain transfer learning.

Convolutional Neural Network Based Detection of Atrial Fibrillation Combing R-R intervals and F-wave Frequency Spectrum.

RespNet: A deep learning model for extraction of respiration from photoplethysmogram.

Spectro-Temporal Feature Based Multi-Channel Convolutional Neural Network for ECG Beat Classification.

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