AIMC Topic: Arrhythmias, Cardiac

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

Computers in biology and medicine Jun 4, 2018
Detecting and classifying cardiac arrhythmias is critical to the diagnosis of patients with cardiac abnormalities. In this paper, a novel approach based on deep learning methodology is proposed for the classification of single-lead electrocardiogram ...
Deep Learning Electrocardiography Signal Processing, Computer-Assisted Arrhythmias, Cardiac Humans Databases, Factual
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Robotic magnetic catheter navigation as a first step in the automation of the ablation procedures for ventricular arrhythmia.

International journal of cardiology May 26, 2018
Arrhythmias, Cardiac Catheter Ablation Magnetics Tachycardia, Ventricular Treatment Outcome Humans Robotics Robotic Surgical Procedures
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Experimental validation of robot-assisted cardiovascular catheterization: model-based versus model-free control.

International journal of computer assisted radiology and surgery Apr 2, 2018
PURPOSE: In cardiac electrophysiology, a long and flexible catheter is delivered to a cardiac chamber for the treatment of arrhythmias. Although several robot-assisted platforms have been commercialized, the disorientation in tele-operation is still ...
Humans Female Robotics Surgery, Computer-Assisted Male Arrhythmias, Cardiac Models, Theoretical Catheter Ablation Printing, Three-Dimensional Reproducibility of Results Cardiac Catheters Cardiac Catheterization Young Adult Adult
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A novel wavelet sequence based on deep bidirectional LSTM network model for ECG signal classification.

Computers in biology and medicine Mar 28, 2018
Long-short term memory networks (LSTMs), which have recently emerged in sequential data analysis, are the most widely used type of recurrent neural networks (RNNs) architecture. Progress on the topic of deep learning includes successful adaptations o...
Arrhythmias, Cardiac Heart Rate Deep Learning Electrocardiography Signal Processing, Computer-Assisted Humans
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A robust deep convolutional neural network for the classification of abnormal cardiac rhythm using single lead electrocardiograms of variable length.

Physiological measurement Mar 27, 2018
OBJECTIVE: Atrial fibrillation (AF) is a major cause of hospitalization and death in the United States. Moreover, as the average age of individuals increases around the world, early detection and diagnosis of AF become even more pressing. In this pap...
Humans Arrhythmias, Cardiac Heart Rate Neural Networks, Computer Electrocardiography Signal Processing, Computer-Assisted
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Multiclass Classification of Cardiac Arrhythmia Using Improved Feature Selection and SVM Invariants.

Computational and mathematical methods in medicine Mar 5, 2018
Arrhythmia is considered a life-threatening disease causing serious health issues in patients, when left untreated. An early diagnosis of arrhythmias would be helpful in saving lives. This study is conducted to classify patients into one of the sixte...
Datasets as Topic Cardiac Conduction System Disease Humans Support Vector Machine Arrhythmias, Cardiac
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Automatic QRS complex detection using two-level convolutional neural network.

Biomedical engineering online Jan 29, 2018
BACKGROUND: The QRS complex is the most noticeable feature in the electrocardiogram (ECG) signal, therefore, its detection is critical for ECG signal analysis. The existing detection methods largely depend on hand-crafted manual features and paramete...
Sensitivity and Specificity Models, Theoretical Electrocardiography Signal-To-Noise Ratio Signal Processing, Computer-Assisted Arrhythmias, Cardiac Humans Neural Networks, Computer Algorithms
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Quantitative Assessment of the Physiological Parameters Influencing QT Interval Response to Medication: Application of Computational Intelligence Tools.

Computational and mathematical methods in medicine Jan 4, 2018
Human heart electrophysiology is complex biological phenomenon, which is indirectly assessed by the measured ECG signal. ECG trace is further analyzed to derive interpretable surrogates including QT interval, QRS complex, PR interval, and T wave morp...
Artificial Intelligence Software Algorithms Action Potentials Risk Models, Statistical Electrophysiology Terfenadine Reproducibility of Results Ions Electrocardiography Sodium Anti-Arrhythmia Agents Regression Analysis Myocytes, Cardiac Programming Languages Clinical Trials as Topic Humans Calcium Heart Observer Variation Arrhythmias, Cardiac Cell Membrane Potassium
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Development of models for predicting Torsade de Pointes cardiac arrhythmias using perceptron neural networks.

BMC bioinformatics Dec 28, 2017
BACKGROUND: Blockage of some ion channels and in particular, the hERG (human Ether-a'-go-go-Related Gene) cardiac potassium channel delays cardiac repolarization and can induce arrhythmia. In some cases it leads to a potentially life-threatening arrh...
ROC Curve Electrocardiography Action Potentials Neural Networks, Computer Myocytes, Cardiac Heart Ventricles Humans Male Models, Cardiovascular Long QT Syndrome Ether-A-Go-Go Potassium Channels Middle Aged Arrhythmias, Cardiac Torsades de Pointes
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A deep convolutional neural network model to classify heartbeats.

Computers in biology and medicine Aug 24, 2017
The electrocardiogram (ECG) is a standard test used to monitor the activity of the heart. Many cardiac abnormalities will be manifested in the ECG including arrhythmia which is a general term that refers to an abnormal heart rhythm. The basis of arrh...
Signal Processing, Computer-Assisted Female Humans Models, Cardiovascular Arrhythmias, Cardiac Male Neural Networks, Computer Heart Rate Electrocardiography Databases, Factual Myocardial Contraction
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