• DocumentCode
    2008080
  • Title

    Cancer Profiles by Affinity Propagation

  • Author

    Ambrogi, Federico ; Raimondi, Elena ; Soria, Daniele ; Boracchi, Patrizia ; Biganzoli, Elia

  • Author_Institution
    Ist. di Statistica Medica e Biometria "GA Maccacaro ", Univ. degli Studi di Milano, Milan
  • fYear
    2008
  • fDate
    11-13 Dec. 2008
  • Firstpage
    650
  • Lastpage
    655
  • Abstract
    The affinity propagation algorithm is applied to a problem of breast cancer subtyping using traditional biologic markers. The algorithm provides a procedure to determine the number of profiles to be considered. A well know breast cancer case series was used to compare the results of the affinity propagation with the results obtained with standard algorithms and indexes for the optimal choice of the number of clusters. Results from affinity propagation are consistent with the results already obtained having the advantage of providing an indication about the number of clusters.
  • Keywords
    cancer; medical computing; pattern clustering; statistical analysis; affinity propagation algorithm; breast cancer subtyping; cancer profiles; clustering techniques; genomic analysis; Bioinformatics; Breast cancer; Clustering algorithms; Computer science; Erbium; Genomics; Inspection; Machine learning; Malignant tumors; Pathology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Applications, 2008. ICMLA '08. Seventh International Conference on
  • Conference_Location
    San Diego, CA
  • Print_ISBN
    978-0-7695-3495-4
  • Type

    conf

  • DOI
    10.1109/ICMLA.2008.110
  • Filename
    4725044