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Feature selection technique applied in Medical application by Supervised algorithm: A Review

Author

Listed:
  • Basna Mohammed Salih Hasan

    (Technical College of Informatics Akre, Duhok Polytechnic University, IT Department, Duhok, Kurdistan Region, Iraq.)

  • Nawzat Sadiq Ahmed

    (Department of Information Technology Management, Technical College of Administration, Duhok University, Kurdistan Region, Iraq.)

Abstract

Feature selection is a strategy for preprocessing that determines the main features of a specific problem. Traditionally, it has been employed across a variety of topics, including biological data analysis, finance, and intrusion detection systems. In addition to minimizing dimensionality, FS was successfully used in medical systems, which often enable one to consider the causes of the disease. In this paper, a review started to describe some basic concepts related to medical applications and provide some necessary background information on feature selection and reviewed more than ten articles of the FS in the medical field that have been introduced and published in the last years.

Suggested Citation

  • Basna Mohammed Salih Hasan & Nawzat Sadiq Ahmed, 2021. "Feature selection technique applied in Medical application by Supervised algorithm: A Review," International Journal of Science and Business, IJSAB International, vol. 5(3), pages 190-203.
    • Handle: RePEc:aif:journl:v:5:y:2021:i:3:p:190-203
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    References listed on IDEAS

    as
    1. n/a, 2019. "Book Reviews," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 2).
    2. Ghaddar, Bissan & Naoum-Sawaya, Joe, 2018. "High dimensional data classification and feature selection using support vector machines," European Journal of Operational Research, Elsevier, vol. 265(3), pages 993-1004.
    3. n/a, 2016. "Book Reviews," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
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