• DocumentCode
    2308897
  • Title

    Machine Learning Applied to BRCA1 Hereditary Breast Cancer Data

  • Author

    Doncescu, Andrei ; Tauzain, Baptiste ; Kabbaj, Nabil

  • Author_Institution
    CNRS, Univ. of Toulouse, Toulouse, France
  • fYear
    2009
  • fDate
    26-29 May 2009
  • Firstpage
    942
  • Lastpage
    947
  • Abstract
    This research aims to provide a tool to doctors in order to help for diagnosis of BRCA1 hereditary breast cancer. Our goal is to determine, if possible, profiles that are responsible for early cancer onset. In order to extract knowledge from the biological information above we will create a relational database that will allow prognosticating cancer apparition. We want to determine different types responsible for different profiles of cancer onset thanks to machine learning programs. The prognostic will rely on polymorphisms of a gene, BRCA1, but on family history as well. The machine learning software(s) will be used as a tool by doctors as a help for diagnosis. This tool will be used in order to determine if these patients are member of a high risk cluster, an early occurring cancer.
  • Keywords
    cancer; learning (artificial intelligence); medical computing; relational databases; BRCA1 hereditary breast cancer data; biological information; cancer apparition prognostication; machine learning; relational database; Breast cancer; Cervical cancer; DNA; Data mining; Genetic mutations; History; Machine learning; Proteins; Surgery; Testing; BRCA1; Heredity; breast cancer; inductive logic programming; polymorphism;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Information Networking and Applications Workshops, 2009. WAINA '09. International Conference on
  • Conference_Location
    Bradford
  • Print_ISBN
    978-1-4244-3999-7
  • Electronic_ISBN
    978-0-7695-3639-2
  • Type

    conf

  • DOI
    10.1109/WAINA.2009.165
  • Filename
    5136772