Gavin S. Chu

Orcid: 0000-0002-5952-8374

According to our database1, Gavin S. Chu authored at least 23 papers between 2013 and 2022.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Bibliography

2022
Can Sequentially Collected Electrograms Be Effectively Used for Dominant Frequency Mapping During Persistent AF?
Proceedings of the Computing in Cardiology, 2022

2021
Unsupervised Classification of Atrial Electrograms for Electroanatomic Mapping of Human Persistent Atrial Fibrillation.
IEEE Trans. Biomed. Eng., 2021

Dominant Frequency and Organization Index for Substrate Identification of Persistent Atrial Fibrillation.
Proceedings of the Computing in Cardiology, CinC 2021, Brno, 2021

2020
Optimizing Atrial Electrogram Classification Based on Local Ablation Outcome in Human Atrial Fibrillation.
Proceedings of the Computing in Cardiology, 2020

2019
Systematic differences of non-invasive dominant frequency estimation compared to invasive dominant frequency estimation in atrial fibrillation.
Comput. Biol. Medicine, 2019

Are Atrial Fibrillation Dominant Frequency Areas the Source of Dominant Excitation Patterns? A Left Atrial Panoramic View.
Proceedings of the 46th Computing in Cardiology, 2019

2018
The temporal behavior and consistency of bipolar atrial electrograms in human persistent atrial fibrillation.
Medical Biol. Eng. Comput., 2018

Unsupervised k-Mean Classification of Atrial Electrograms From Human Persistent Atrial Fibrillation.
Proceedings of the Computing in Cardiology, 2018

Dominant Frequency Variability Mapping for Identifying Stable Drivers During Persistent Atrial Fibrillation Using Noncontact Mapping.
Proceedings of the Computing in Cardiology, 2018

A K-Nearest Neighbours Classifier for Predicting Catheter Ablation Responses Using Noncontact Electrograms During Persistent Atrial Fibrillation.
Proceedings of the Computing in Cardiology, 2018

2017
An interactive platform to guide catheter ablation in human persistent atrial fibrillation using dominant frequency, organization and phase mapping.
Comput. Methods Programs Biomed., 2017

Deterministic Structures in Fractionated Atrial Electrograms During Human Persistent Atrial Fibrillation.
Proceedings of the Computing in Cardiology, 2017

2016
Minimizing discordances in automated classification of fractionated electrograms in human persistent atrial fibrillation.
Medical Biol. Eng. Comput., 2016

Dynamic Behavior of Rotors during Human Persistent Atrial Fibrillation as observed using Non-Contact Mapping.
Proceedings of the Computing in Cardiology, CinC 2016, Vancouver, 2016

Contributing Factors Concerning Inconsistencies in Persistent Atrial Fibrillation Ablation Outcomes.
Proceedings of the Computing in Cardiology, CinC 2016, Vancouver, 2016

2015
Drifting Rotors Prevalence Is Associated with Dominant Frequency Reduction after Persistent Atrial Fibrillation Ablation.
Proceedings of the Computing in Cardiology, 2015

Investigation on Recurrent High Dominant Frequency Spatiotemporal Patterns during Persistent Atrial Fibrillation.
Proceedings of the Computing in Cardiology, 2015

Combination of Frequency and Phase to Characterise the Spatiotemporal Behaviour of Cardiac Waves during Persistent Atrial Fibrillation in Humans.
Proceedings of the Computing in Cardiology, 2015

Unifying Automated Fractionated Atrial Electrograms Classification using Electroanatomical Mapping Systems in Persistent Atrial Fibrillation Studies.
Proceedings of the Computing in Cardiology, 2015

2014
A Platform to guide Catheter Ablation of Persistent Atrial Fibrillation using Dominant Frequency Mapping.
Proceedings of the Computing in Cardiology, CinC 2014, 2014

Spatiotemporal Behaviour of High Dominant Frequency during Persistent Atrial Fibrillation.
Proceedings of the Computing in Cardiology, CinC 2014, 2014

2013
Analysis of Spatial Variability for the Development of Reduced Lead Body Surface Maps.
Proceedings of the Computing in Cardiology, 2013

Different Definitions of Complex Fractionated Atrial Electrograms do not Concur with Clinical Perspective.
Proceedings of the Computing in Cardiology, 2013


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