AIMC Topic: Arrhythmias, Cardiac

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CEFEs: A CNN Explainable Framework for ECG Signals.

Artificial intelligence in medicine Mar 26, 2021
In the healthcare domain, trust, confidence, and functional understanding are critical for decision support systems, therefore, presenting challenges in the prevalent use of black-box deep learning (DL) models. With recent advances in deep learning m...
Neural Networks, Computer Electrocardiography Arrhythmias, Cardiac Humans
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Hybrid Prediction Method for ECG Signals Based on VMD, PSR, and RBF Neural Network.

BioMed research international Mar 15, 2021
To explore a method to predict ECG signals in body area networks (BANs), we propose a hybrid prediction method for ECG signals in this paper. The proposed method combines variational mode decomposition (VMD), phase space reconstruction (PSR), and a r...
Databases, Factual Humans Arrhythmias, Cardiac Electrocardiography Neural Networks, Computer Signal Processing, Computer-Assisted
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Machine Learning in Arrhythmia and Electrophysiology.

Circulation research Feb 18, 2021
Machine learning (ML), a branch of artificial intelligence, where machines learn from big data, is at the crest of a technological wave of change sweeping society. Cardiovascular medicine is at the forefront of many ML applications, and there is a si...
Humans Machine Learning Animals Electrophysiologic Techniques, Cardiac Decision Support Systems, Clinical Arrhythmias, Cardiac Models, Cardiovascular
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A Hybrid Deep CNN Model for Abnormal Arrhythmia Detection Based on Cardiac ECG Signal.

Sensors (Basel, Switzerland) Feb 1, 2021
Electrocardiogram (ECG) signals play a vital role in diagnosing and monitoring patients suffering from various cardiovascular diseases (CVDs). This research aims to develop a robust algorithm that can accurately classify the electrocardiogram signal ...
Neural Networks, Computer Algorithms Electrocardiography Humans Arrhythmias, Cardiac Heart Rate
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Smartwatch Electrocardiogram and Artificial Intelligence for Assessing Cardiac-Rhythm Safety of Drug Therapy in the COVID-19 Pandemic. The QT-logs study.

International journal of cardiology Jan 29, 2021
BACKGROUND: QTc interval monitoring, for the prevention of drug-induced arrhythmias is necessary, especially in the context of coronavirus disease 2019 (COVID-19). For the provision of widespread use, surrogates for 12‑lead ECG QTc assessment may be ...
Electrocardiography Azithromycin Long QT Syndrome Arrhythmias, Cardiac COVID-19 Drug Treatment Adult Hydroxychloroquine Male Middle Aged Pandemics Female Humans Artificial Intelligence
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Machine learning method for predicting pacemaker implantation following transcatheter aortic valve replacement.

Pacing and clinical electrophysiology : PACE Jan 28, 2021
BACKGROUND: An accurate assessment of permanent pacemaker implantation (PPI) risk following transcatheter aortic valve replacement (TAVR) is important for clinical decision making. The aims of this study were to investigate the significance and utili...
Forecasting Retrospective Studies Female Humans Machine Learning Risk Assessment Postoperative Complications Logistic Models Aged Aged, 80 and over Male Transcatheter Aortic Valve Replacement Prosthesis Implantation Pacemaker, Artificial Aortic Valve Stenosis Arrhythmias, Cardiac
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Demonstration of the potential of white-box machine learning approaches to gain insights from cardiovascular disease electrocardiograms.

PloS one Dec 17, 2020
We present the results from a white-box machine learning approach to detect cardiac arrhythmias using electrocardiographic data. A C5.0 is trained to recognize four classes using common features. The four classes are (i) atrial fibrillation and atria...
Arrhythmias, Cardiac Algorithms Humans Aged, 80 and over Female Adult Machine Learning Male Aged Middle Aged Electrocardiography
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Noise robust automatic heartbeat classification system using support vector machine and conditional spectral moment.

Physical and engineering sciences in medicine Nov 24, 2020
Heartbeat classification is central to the detection of the arrhythmia. For the effective heartbeat classification, the noise-robust features are very significant. In this work, we have proposed a noise-robust support vector machine (SVM) based heart...
Humans Heart Rate Support Vector Machine Arrhythmias, Cardiac
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Classification of normal sinus rhythm, abnormal arrhythmia and congestive heart failure ECG signals using LSTM and hybrid CNN-SVM deep neural networks.

Computer methods in biomechanics and biomedical engineering Sep 21, 2020
Effective monitoring of heart patients according to heart signals can save a huge amount of life. In the last decade, the classification and prediction of heart diseases according to ECG signals has gained great importance for patients and doctors. I...
Arrhythmias, Cardiac Signal Processing, Computer-Assisted Neural Networks, Computer Heart Failure Algorithms Middle Aged Young Adult Female Electrocardiography Adult Humans Support Vector Machine Male
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Accurate deep neural network model to detect cardiac arrhythmia on more than 10,000 individual subject ECG records.

Computer methods and programs in biomedicine Sep 8, 2020
BACKGROUND AND OBJECTIVE: Cardiac arrhythmia, which is an abnormal heart rhythm, is a common clinical problem in cardiology. Detection of arrhythmia on an extended duration electrocardiogram (ECG) is done based on initial algorithmic software screeni...
Software Algorithms Electrocardiography Signal Processing, Computer-Assisted Arrhythmias, Cardiac Humans Neural Networks, Computer
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