• DocumentCode
    3724961
  • Title

    Diabetes determination via vortex optimization algorithm based support vector machines

  • Author

    Utku K?se;G?r Emre G?raks?n;?mer Deperlio?lu

  • Author_Institution
    Bilgisayar Bilimleri Uygulama ve Ara?t?rma Merkezi, U?ak ?niversitesi, Turkey
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Approaches performed based on computer supported systems within the medical field gain more popularity day by day. In such systems, Artificial Intelligence techniques are often used for several disease diagnostics. Diabetes is one of these diseases. In this study, a diabetes diagnosis system based on Support Vector Machines has been proposed. Along training of SVM, Vortex Optimization Algorithm was used for determining the sigma parameter of the Gauss (RBF) kernel function, and a classification process has been done over the diabetes data set related to Pima Indians.
  • Keywords
    "Support vector machines","Artificial intelligence","Medical diagnosis","Diabetes","Medical diagnostic imaging","Diseases","Optimization"
  • Publisher
    ieee
  • Conference_Titel
    Medical Technologies National Conference (TIPTEKNO), 2015
  • Type

    conf

  • DOI
    10.1109/TIPTEKNO.2015.7374614
  • Filename
    7374614