AIMC Topic: Tachycardia, Ventricular

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Prediction of Ventricular Tachycardia One Hour before Occurrence Using Artificial Neural Networks.

Scientific reports Aug 26, 2016
Ventricular tachycardia (VT) is a potentially fatal tachyarrhythmia, which causes a rapid heartbeat as a result of improper electrical activity of the heart. This is a potentially life-threatening arrhythmia because it can cause low blood pressure an...
Monitoring, Ambulatory Tachycardia, Ventricular Respiratory Rate Humans Sensitivity and Specificity Neural Networks, Computer Prognosis Heart Rate Early Diagnosis Reproducibility of Results
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Detection of Shockable Ventricular Arrhythmia using Variational Mode Decomposition.

Journal of medical systems Jan 21, 2016
Ventricular tachycardia (VT) and ventricular fibrillation (VF) are shockable ventricular cardiac ailments. Detection of VT/VF is one of the important step in both automated external defibrillator (AED) and implantable cardioverter defibrillator (ICD)...
Algorithms Sensitivity and Specificity Image Processing, Computer-Assisted Defibrillators Electrocardiography Humans Tachycardia, Ventricular Machine Learning Ventricular Fibrillation
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Automatic supporting system for regionalization of ventricular tachycardia exit site in implantable defibrillators.

PloS one Apr 24, 2015
Electrograms stored in Implantable Cardioverter Defibrillators (ICD-EGM) have been proven to convey useful information for roughly determining the anatomical location of the Left Ventricular Tachycardia exit site (LVTES). Our aim here was to evaluate...
Middle Aged Support Vector Machine Reproducibility of Results Humans Electrocardiography Tachycardia, Ventricular Female Defibrillators, Implantable Aged Male
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Near-term prediction of sustained ventricular arrhythmias applying artificial intelligence to single-lead ambulatory electrocardiogram.

European heart journal Jun 2, 2025
BACKGROUND AND AIMS: Accurate near-term prediction of life-threatening ventricular arrhythmias would enable pre-emptive actions to prevent sudden cardiac arrest/death. A deep learning-enabled single-lead ambulatory electrocardiogram (ECG) may identif...
Female Electrocardiography, Ambulatory Humans Aged Middle Aged Tachycardia, Ventricular Artificial Intelligence Male Risk Assessment Death, Sudden, Cardiac Retrospective Studies Deep Learning
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A DenseNet-based Abnormal Ventricular Potentials Onset Delineation: A Feasibility Study.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Abnormal ventricular potentials (AVPs) are fractionated and complex electrograms (EGMs), typically associated with slow conduction areas in the myocardium. As such, in ventricular tachycardia (VT), their identification supports the localization of th...
Electrocardiography Signal Processing, Computer-Assisted Feasibility Studies Humans Neural Networks, Computer Convolutional Neural Networks Heart Ventricles Tachycardia, Ventricular
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A Hybrid GCN-LSTM Model for Ventricular Arrhythmia Classification Based on ECG Pattern Similarity.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Accurate differentiation between Ventricular Tachycardia (VT) and Ventricular Fibrillation (VF) is essential in the field of cardiology. Recent advancements in deep learning have facilitated automated arrhythmia recognition, surpassing traditional el...
Electrocardiography Signal Processing, Computer-Assisted Arrhythmias, Cardiac Tachycardia, Ventricular Ventricular Fibrillation Humans Neural Networks, Computer Algorithms
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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.

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology Feb 16, 2023
AIMS: Existing strategies that identify post-infarct ventricular tachycardia (VT) ablation target either employ invasive electrophysiological (EP) mapping or non-invasive modalities utilizing the electrocardiogram (ECG). Their success relies on local...
Tachycardia, Ventricular Electrophysiologic Techniques, Cardiac Infarction Electrocardiography Catheter Ablation Humans Deep Learning
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The Feasibility of Arrhythmias Detection from A Capacitive ECG Measurement Using Convolutional Neural Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Capacitive ECG (cECG) can measure the cardiac electrical signal via capacitive coupling between electrodes and skin. This unconstrained measurement is suitable for personal heart monitoring; however, the instability in the quality of the signal hinde...
Electrocardiography Feasibility Studies Tachycardia, Ventricular Ventricular Fibrillation Humans Neural Networks, Computer
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Predicting electrical storms by remote monitoring of implantable cardioverter-defibrillator patients using machine learning.

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology Feb 1, 2019
AIMS: Electrical storm (ES) is a serious arrhythmic syndrome that is characterized by recurrent episodes of ventricular arrhythmias. Electrical storm is associated with increased mortality and morbidity despite the use of implantable cardioverter-def...
Ventricular Fibrillation Defibrillators, Implantable Electric Countershock Humans Predictive Value of Tests Risk Assessment Machine Learning Remote Sensing Technology Time Factors Databases, Factual Heart Failure Signal Processing, Computer-Assisted Treatment Outcome Reproducibility of Results Heart Rate Risk Factors Tachycardia, Ventricular
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