• DocumentCode
    476045
  • Title

    Detection of increased level of chromosome breakage in peripheral blood of Iranian women with sporadic breast cancer using neural networks

  • Author

    Fooladi, Somaye ; Khaloozadeh, Hamid ; Behjati, Farkhondeh

  • Author_Institution
    K.N.Toosi Univ. of Technol., Tehran
  • Volume
    3
  • fYear
    2008
  • fDate
    12-15 July 2008
  • Firstpage
    1227
  • Lastpage
    1231
  • Abstract
    Elevation of radiosensitivity may be a marker for breast cancer predisposition. This paper shows that the sensitivity to the induction of chromosomal damage by ionizing Gama Exposure is, on average higher in breast cancer patients than of normal healthy controls [1]. In order to investigation of gamma effect in each person´s lymphocytes and comparison between two groups, seventy two hours after blood sample culturing, the samples are exposed by gamma rays and they are harvested. Gamma exposure causes aberrations in chromosomes. Our database includes chromosome breakage in seven chromosome groups and age of patients. Principle Component Analysis (PCA) is used for feature selection stage. Then we used an Artificial Neural Networks (ANN) for classification of normal cases from abnormal cases. Satisfactory result obtained with an accuracy rate of 93.09% for Neural Networks (NN) classifier.
  • Keywords
    blood; cancer; medical diagnostic computing; neural nets; principal component analysis; Iranian women; artificial neural networks; chromosome breakage; gamma exposure; peripheral blood; principle component analysis; radiosensitivity elevation; sporadic breast cancer; Artificial neural networks; Biological cells; Blood; Breast cancer; Cancer detection; Cells (biology); Cybernetics; Machine learning; Neural networks; Principal component analysis; Artificial neural networks; Breast cancers; Chromosome breakage; Pattern recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2008 International Conference on
  • Conference_Location
    Kunming
  • Print_ISBN
    978-1-4244-2095-7
  • Electronic_ISBN
    978-1-4244-2096-4
  • Type

    conf

  • DOI
    10.1109/ICMLC.2008.4620592
  • Filename
    4620592