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Nature Inspired Concepts in Long-Term Electrocardiogram Clustering

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F08%3A03151590" target="_blank" >RIV/68407700:21230/08:03151590 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Nature Inspired Concepts in Long-Term Electrocardiogram Clustering

  • Original language description

    In this paper we compare and evaluate the use of clustering approaches that use nature inspired concepts. The following methods are considered: Ant Colony inspired Clustering, Ant Colony inspired method for Decision Tree generation, Radial Basis FunctionNeural Networks with different learning algorithms. We compare the nature inspired methods to classical approaches, such as hierarchical clustering and k-means. The best-performing method over the whole dataset has been agglomerative hierarchical clustering (Se=94.3, Sp=74.1), however it is practically unusable as it is memory and computational demanding. Acceptable results (complexity vs. error) have been obtained by the Ant-Colony inspired method for Decision tree generation (Se=93.1, Sp=72.8).

  • Czech name

    Použití přírodou inspirovaných konceptů při shlukování dlouhodobých záznamů EKG

  • Czech description

    V tomto příspěvku jsou porovnávány a vyhodnocovány metody shlukování, které využívají přírodou inspirované koncepty.

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JC - Computer hardware and software

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2008

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    IFMBE Proceedings

  • ISBN

    978-3-540-89207-6

  • ISSN

    1680-0737

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

  • Publisher name

    Springer

  • Place of publication

    Berlin

  • Event location

    Antwerp

  • Event date

    Nov 23, 2008

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article