AIMC Topic: Electrophysiologic Techniques, Cardiac

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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...
Models, Cardiovascular Electrophysiologic Techniques, Cardiac Machine Learning Animals Decision Support Systems, Clinical Arrhythmias, Cardiac Humans
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Machine Learned Cellular Phenotypes in Cardiomyopathy Predict Sudden Death.

Circulation research Nov 10, 2020
RATIONALE: Susceptibility to VT/VF (ventricular tachycardia/fibrillation) is difficult to predict in patients with ischemic cardiomyopathy either by clinical tools or by attempting to translate cellular mechanisms to the bedside.
Humans Female Risk Factors Aged Aged, 80 and over Neural Networks, Computer Phenotype Prospective Studies Prognosis Signal Processing, Computer-Assisted Myocardial Infarction Tachycardia, Ventricular Time Factors Male Cardiomyopathies Ventricular Fibrillation Support Vector Machine Middle Aged Action Potentials Risk Assessment Predictive Value of Tests Diagnosis, Computer-Assisted Death, Sudden, Cardiac Electrophysiologic Techniques, Cardiac
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Optical Mapping-Validated Machine Learning Improves Atrial Fibrillation Driver Detection by Multi-Electrode Mapping.

Circulation. Arrhythmia and electrophysiology Sep 13, 2020
BACKGROUND: Atrial fibrillation (AF) can be maintained by localized intramural reentrant drivers. However, AF driver detection by clinical surface-only multielectrode mapping (MEM) has relied on subjective interpretation of activation maps. We hypoth...
Fourier Analysis Electrophysiologic Techniques, Cardiac Voltage-Sensitive Dye Imaging Action Potentials Predictive Value of Tests Atrial Fibrillation Heart Rate Humans Machine Learning Reproducibility of Results Spectroscopy, Near-Infrared Time Factors
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Machine Learning to Classify Intracardiac Electrical Patterns During Atrial Fibrillation: Machine Learning of Atrial Fibrillation.

Circulation. Arrhythmia and electrophysiology Jul 6, 2020
BACKGROUND: Advances in ablation for atrial fibrillation (AF) continue to be hindered by ambiguities in mapping, even between experts. We hypothesized that convolutional neural networks (CNN) may enable objective analysis of intracardiac activation i...
Humans Neural Networks, Computer Female Reproducibility of Results Aged Male Middle Aged Diagnosis, Computer-Assisted Pattern Recognition, Automated Signal Processing, Computer-Assisted Atrial Function, Left Registries Time Factors Electrophysiologic Techniques, Cardiac Atrial Fibrillation Support Vector Machine Atrial Function, Right Heart Rate Action Potentials Predictive Value of Tests
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Artificial Intelligence and Machine Learning in Arrhythmias and Cardiac Electrophysiology.

Circulation. Arrhythmia and electrophysiology Jul 6, 2020
Artificial intelligence (AI) and machine learning (ML) in medicine are currently areas of intense exploration, showing potential to automate human tasks and even perform tasks beyond human capabilities. Literacy and understanding of AI/ML methods are...
Arrhythmias, Cardiac Heart Rate Humans Electrophysiologic Techniques, Cardiac Artificial Intelligence Machine Learning Action Potentials Prognosis Predictive Value of Tests Reproducibility of Results Signal Processing, Computer-Assisted Diagnosis, Computer-Assisted Heart Conduction System Deep Learning Electrocardiography
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Strain Curve Classification Using Supervised Machine Learning Algorithm with Physiologic Constraints.

Ultrasound in medicine & biology Jun 4, 2020
Speckle tracking echocardiography (STE) enables quantification of myocardial deformation by a generation of spatiotemporal strain curves or time-strain curves (TSCs). Currently, only assessment of peak global longitudinal strain is employed in clinic...
Echocardiography Humans Heart Female Supervised Machine Learning Adult Electrophysiologic Techniques, Cardiac Male
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Rethinking multiscale cardiac electrophysiology with machine learning and predictive modelling.

Computers in biology and medicine Oct 18, 2018
We review some of the latest approaches to analysing cardiac electrophysiology data using machine learning and predictive modelling. Cardiac arrhythmias, particularly atrial fibrillation, are a major global healthcare challenge. Treatment is often th...
Atrial Fibrillation Humans Catheter Ablation Machine Learning Models, Cardiovascular Electrocardiography Electrophysiologic Techniques, Cardiac Heart Conduction System
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Catheter Ablation of Focal Atrial Tachycardia Using Remote Magnetic Navigation.

The Journal of invasive cardiology Dec 15, 2017
OBJECTIVES: The outcomes of catheter ablation in focal atrial tachycardia (AT) using remote magnetic navigation (RMN) are still controversial. The objectives of this study were to assess the acute and long-term outcomes of catheter ablation in focal ...
Catheter Ablation Humans Magnetics Retrospective Studies Electrophysiologic Techniques, Cardiac Female Tachycardia, Ectopic Atrial Adult Robotics Male Equipment Design Middle Aged Fluoroscopy Treatment Outcome Surgery, Computer-Assisted Follow-Up Studies
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Semi-supervised clustering of fractionated electrograms for electroanatomical atrial mapping.

Biomedical engineering online Apr 26, 2016
BACKGROUND: Electrogram-guided ablation procedures have been proposed as an alternative strategy consisting of either mapping and ablating focal sources or targeting complex fractionated electrograms in atrial fibrillation (AF). However, the incomple...
Supervised Machine Learning Humans Heart Atria Databases, Factual Nonlinear Dynamics Cluster Analysis Electrophysiologic Techniques, Cardiac Signal Processing, Computer-Assisted
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State of the Art of Artificial Intelligence in Clinical Electrophysiology in 2025: A Scientific Statement of the European Heart Rhythm Association (EHRA) of the ESC, the Heart Rhythm Society (HRS), and the ESC Working Group on E-Cardiology.

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 May 7, 2025
AIMS: Artificial intelligence (AI) has the potential to transform cardiac electrophysiology (EP), particularly in arrhythmia detection, procedural optimization, and patient outcome prediction. However, a standardized approach to reporting and underst...
Humans Artificial Intelligence Checklist Death, Sudden, Cardiac Electrophysiologic Techniques, Cardiac Cardiac Electrophysiology Delphi Technique Consensus Arrhythmias, Cardiac Atrial Fibrillation
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