• DocumentCode
    2635754
  • Title

    Knowledge modeling methods in the framework of evidence theory: an experimental comparison for melanoma detection

  • Author

    Lefevre, Eric ; Colot, Olivier ; Vannoorenberghe, Patrick ; De Brucq, Denis

  • Author_Institution
    PSI, Rouen Univ., Mont-Saint-Aignan, France
  • Volume
    4
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    2806
  • Abstract
    The Dempster-Shafer theory, or evidence theory, is used in different fields such as data fusion, regression or classification. Within the framework of this theory, uncertain and imprecise data are represented using belief functions. Data fusion operators as well as the decision rule of this theory were largely developed and formalized. The aim of the paper is to present modeling methods of knowledge for the initialization of belief functions. Moreover, an experimental comparison of these different modeling methods on real data extracted from images of dermatological lesions is presented
  • Keywords
    belief maintenance; cancer; inference mechanisms; medical expert systems; skin; uncertainty handling; Dempster-Shafer theory; belief functions; data fusion; data fusion operators; decision rule; dermatological lesion images; evidence theory; imprecise data; knowledge modeling methods; melanoma detection; modeling methods; real data; Attenuation; Data analysis; Data mining; Equations; Lesions; Malignant tumors; Probability distribution; Reliability theory; Upper bound;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 2000 IEEE International Conference on
  • Conference_Location
    Nashville, TN
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-6583-6
  • Type

    conf

  • DOI
    10.1109/ICSMC.2000.884422
  • Filename
    884422