Breast Cancer Prognosis Using Learning Vector Quantization Neural Network Technique

  • Authors

    • W. Abdul Hameed
    • Raja Das
    • Jitendra Jaiswal
    2018-10-02
    https://doi.org/10.14419/ijet.v7i4.10.26789
  • Neural networks, Learning Vector Quantization, Breast cancer Prognosis, recurrence / non-recurrence, Classification.

  • Abstract

    A suitable treatment coming after surgery is very much motivated by prognosis - the speculated outcome of the disease. Now-a-days improving prognostic prediction is a challenging task to the doctors. This paper presents prognosis for the breast cancer issues by applying Neural Network Architecture with the dataset for Wisconsin Prognostic Breast Cancer. The accuracy is evaluated by adopting algorithm for Kohonen’s first issue of Learning Vector Quantization to predict the recurrence of the disease within 2 years or beyond and also within 5 years or beyond.

     

     

  • References

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  • How to Cite

    Abdul Hameed, W., Das, R., & Jaiswal, J. (2018). Breast Cancer Prognosis Using Learning Vector Quantization Neural Network Technique. International Journal of Engineering & Technology, 7(4.10), 922-924. https://doi.org/10.14419/ijet.v7i4.10.26789

    Received date: 2019-01-30

    Accepted date: 2019-01-30

    Published date: 2018-10-02