Cardiovascular

Arrhythmias

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

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Accurate deep neural network model to detect cardiac arrhythmia on more than 10,000 individual subject ECG records.

BACKGROUND AND OBJECTIVE: Cardiac arrhythmia, which is an abnormal heart rhythm, is a common clinica...

Sep 2020 32932129
Machine learning techniques for detecting electrode misplacement and interchanges when recording ECGs: A systematic review and meta-analysis.

INTRODUCTION: Electrode misplacement and interchange errors are known problems when recording the 12...

Aug 2020 32866909
CNN and LSTM-Based Emotion Charting Using Physiological Signals.

Novel trends in affective computing are based on reliable sources of physiological signals such as E...

Aug 2020 32823807
Machine learning-based prediction of acute coronary syndrome using only the pre-hospital 12-lead electrocardiogram.

Prompt identification of acute coronary syndrome is a challenge in clinical practice. The 12-lead el...

Aug 2020 32769990
ECG Biometrics Using Deep Learning and Relative Score Threshold Classification.

The field of biometrics is a pattern recognition problem, where the individual traits are coded, reg...

Jul 2020 32707861
Toward Task Autonomy in Robotic Cardiac Ablation: Learning-Based Kinematic Control of Soft Tendon-Driven Catheters.

The goal of this study was to propose and validate a control framework with level-2 autonomy (task a...

Jul 2020 32678722
Using the VQ-VAE to improve the recognition of abnormalities in short-duration 12-lead electrocardiogram records.

BACKGROUND AND OBJECTIVE: Morphological diagnosis is a basic clinical task of the short-duration 12-...

Jul 2020 32674047
An Efficient and Robust Deep Learning Method with 1-D Octave Convolution to Extract Fetal Electrocardiogram.

The invasive method of fetal electrocardiogram (fECG) monitoring is widely used with electrodes dire...

Jul 2020 32635568
Continuous blood pressure measurement from one-channel electrocardiogram signal using deep-learning techniques.

Continuous blood pressure (BP) measurement is crucial for reliable and timely hypertension detection...

Jun 2020 32972654
Machine learning-based risk prediction of intrahospital clinical outcomes in patients undergoing TAVI.

BACKGROUND: Currently, patient selection in TAVI is based upon a multidisciplinary heart team assess...

Jun 2020 32583062
Assessing the perforation site of cardiac tamponade during radiofrequency catheter ablation using gas analysis of pericardial effusion.

BACKGROUND: The incidence of pericardial effusion (PE) during radiofrequency catheter ablation (CA) ...

Jun 2020 34113880
Artificial Neural Network for Atrial Fibrillation Identification in Portable Devices.

Atrial fibrillation (AF) is a common cardiac disorder that can cause severe complications. AF diagno...

Jun 2020 32599796
Missing Value Estimation Methods Research for Arrhythmia Classification Using the Modified Kernel Difference-Weighted KNN Algorithms.

Electrocardiogram (ECG) signal is critical to the classification of cardiac arrhythmia using some ma...

Jun 2020 32685521
Artificial Intelligence-Enabled ECG: a Modern Lens on an Old Technology.

PURPOSE OF REVIEW: To (i) review the concept of artificial intelligence (AI); (ii) summarize recent ...

Jun 2020 32562154
How Will Machine Learning Inform the Clinical Care of Atrial Fibrillation?

Machine learning applications in cardiology have rapidly evolved in the past decade. With the availa...

Jun 2020 32833571
Machine Learning of 12-Lead QRS Waveforms to Identify Cardiac Resynchronization Therapy Patients With Differential Outcomes.

BACKGROUND: Cardiac resynchronization therapy (CRT) improves heart failure outcomes but has signific...

Jun 2020 32538136
Opportunities and challenges of deep learning methods for electrocardiogram data: A systematic review.

BACKGROUND: The electrocardiogram (ECG) is one of the most commonly used diagnostic tools in medicin...

Jun 2020 32658725
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