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Description
  • Detection of Atrial fibrillation and identification of complex fractionated atrial electrograms (CFAEs) sites is important part of the development of new AF ablation strategies. CFAE may represent the electrophysiological substrate for atrial fibrillation (AF). Signal processing algorithms are the key part of this task. Artificial intelligence (AI) algorithms for automated description of atrial electrograms (A-EGMs) fractionation based on wavelet transform and several feature extraction methods and statistical pattern recognition was proposed and methodology of A-EGM processing was designed and tested. The AI algorithms used here for signal processing, description and classification were developed and validated. AI algorithms used and tested here showed promising results of A-EGM classification of highly fractionated A-EGMs.
  • Detection of Atrial fibrillation and identification of complex fractionated atrial electrograms (CFAEs) sites is important part of the development of new AF ablation strategies. CFAE may represent the electrophysiological substrate for atrial fibrillation (AF). Signal processing algorithms are the key part of this task. Artificial intelligence (AI) algorithms for automated description of atrial electrograms (A-EGMs) fractionation based on wavelet transform and several feature extraction methods and statistical pattern recognition was proposed and methodology of A-EGM processing was designed and tested. The AI algorithms used here for signal processing, description and classification were developed and validated. AI algorithms used and tested here showed promising results of A-EGM classification of highly fractionated A-EGMs. (en)
Title
  • Evaluation of Atrial Fibrillation in Human Using Artificial Intelligence Methods
  • Evaluation of Atrial Fibrillation in Human Using Artificial Intelligence Methods (en)
skos:prefLabel
  • Evaluation of Atrial Fibrillation in Human Using Artificial Intelligence Methods
  • Evaluation of Atrial Fibrillation in Human Using Artificial Intelligence Methods (en)
skos:notation
  • RIV/68407700:21230/10:00177120!RIV11-MSM-21230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM6840770012)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 257802
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/10:00177120
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Classification; signal processing; AEGM; atrial fibrillation (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [019C385B688C]
http://linked.open...v/mistoKonaniAkce
  • Vienna
http://linked.open...i/riv/mistoVydani
  • Vienna
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the Twentieth European Meeting on Cybernetics and Systems Research
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Lhotská, Lenka
  • Křemen, Václav
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • Austrian Society for Cybernetics Studies
https://schema.org/isbn
  • 978-3-85206-178-8
http://localhost/t...ganizacniJednotka
  • 21230
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