• DocumentCode
    1605139
  • Title

    Comparative study of fuzzy methods in breast cancer diagnosis

  • Author

    Fuentes-Uriarte, J. ; García, M. ; Castillo, O.

  • Author_Institution
    Div. of Res. & Grad. Studies, Tijuana Inst. of Technol., Tijuana
  • fYear
    2008
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper describes a comparison of results in breast cancer diagnosis, using two fuzzy logic methods; the first case uses fuzzy clustering with the fuzzy c-means (FCM) algorithm, which tries to find similarities between different variables; the second method is an implementation of a fuzzy inference system (FIS) with a genetic algorithm (GA) for creating and activating the optimal rules.
  • Keywords
    cancer; fuzzy logic; fuzzy reasoning; fuzzy set theory; genetic algorithms; medical diagnostic computing; pattern clustering; breast cancer diagnosis; fuzzy c-means algorithm; fuzzy clustering; fuzzy inference system; fuzzy logic method; genetic algorithm; Artificial intelligence; Breast cancer; Databases; Fuzzy logic; Fuzzy sets; Fuzzy systems; Genetic algorithms; Humans; Medical diagnostic imaging; Needles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Information Processing Society, 2008. NAFIPS 2008. Annual Meeting of the North American
  • Conference_Location
    New York City, NY
  • Print_ISBN
    978-1-4244-2351-4
  • Electronic_ISBN
    978-1-4244-2352-1
  • Type

    conf

  • DOI
    10.1109/NAFIPS.2008.4531337
  • Filename
    4531337