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Description
  • Paper presents the use and comparison of promising nature-inspired methods which can contribute in the ECG interpretation process. Heart-beat clustering can effectively reduce the amount of data presented to the cardiologist: cardiac arrhythmias and significant morphology changes in the ECG can be visually emphasized in a reasonable time. The exhaustive clustering methods are resource demanding (in terms of computational time and memory), therefore appropriate heuristics should be considered. The nature-inspired methods are currently in the focus of intensive research work. This paper presents the use of ant-colony inspired metaheuristics for data clustering. The method is compared with well known clustering techniques (both classical and nature-inspired), first testing on the known dataset and finally applying them to the real ECG data records from the MIT-BIH database.
  • Paper presents the use and comparison of promising nature-inspired methods which can contribute in the ECG interpretation process. Heart-beat clustering can effectively reduce the amount of data presented to the cardiologist: cardiac arrhythmias and significant morphology changes in the ECG can be visually emphasized in a reasonable time. The exhaustive clustering methods are resource demanding (in terms of computational time and memory), therefore appropriate heuristics should be considered. The nature-inspired methods are currently in the focus of intensive research work. This paper presents the use of ant-colony inspired metaheuristics for data clustering. The method is compared with well known clustering techniques (both classical and nature-inspired), first testing on the known dataset and finally applying them to the real ECG data records from the MIT-BIH database. (en)
  • Článek popisuje využití a srovnání významných metod inspirovaných přírodou, které lze využít v procesu interpretace EKG. Pomocí shlukování srdečních akcí lze ulehčit práci expertovi - kardiologovi. Metody, které prohledávají celý stavový prostor, jsou časově a výpočetně náročné, a proto je vhodné použít vhodné heuristické přístupy. Článek popisuje metodu, inspirovanou mravenčími koloniemi a srovnává ji s klasickými (i přírodou inspirovanými) technikami. Použity byly záznamy EKG z volně dostupné databáze MIT-BIH. (cs)
Title
  • Heart signal processing using artificial intelligence methods
  • Heart signal processing using artificial intelligence methods (en)
  • Zpracování signálů srdce s využitím metod umělé inteligence (cs)
skos:prefLabel
  • Heart signal processing using artificial intelligence methods
  • Heart signal processing using artificial intelligence methods (en)
  • Zpracování signálů srdce s využitím metod umělé inteligence (cs)
skos:notation
  • RIV/68407700:21230/08:03151585!RIV09-MSM-21230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(1ET201210527), V
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
  • 369888
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/08:03151585
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • ECG; ant colony; clustering; data mining; expert systems; optimization (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [25CDF601F69E]
http://linked.open...v/mistoKonaniAkce
  • Praha
http://linked.open...i/riv/mistoVydani
  • Praha
http://linked.open...i/riv/nazevZdroje
  • Proceedings of Workshop 2008
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Burša, Miroslav
  • Lhotská, Lenka
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • České vysoké učení technické v Praze
https://schema.org/isbn
  • 978-80-01-04016-4
http://localhost/t...ganizacniJednotka
  • 21230
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