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Improving the Accuracy of Misclassified Breast Cancer Data Using Machine Learning

Author

Listed:
  • Rong-Ho Lin
  • Benjamin Kofi Kujabi

    (Department of Industrial Engineering and Management, National Taipei University of Technology, Taiwan)

Abstract

Breast cancer is the most common cancer among women. Many studies have made significant gains...

Suggested Citation

  • Rong-Ho Lin & Benjamin Kofi Kujabi, 2022. "Improving the Accuracy of Misclassified Breast Cancer Data Using Machine Learning," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 42(2), pages 33435-33442, March.
    • Handle: RePEc:abf:journl:v:42:y:2022:i:2:p:33435-33442
    DOI: 10.26717/BJSTR.2022.42.006722
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    References listed on IDEAS

    as
    1. Zhuang, Zoe Y. & Churilov, Leonid & Burstein, Frada & Sikaris, Ken, 2009. "Combining data mining and case-based reasoning for intelligent decision support for pathology ordering by general practitioners," European Journal of Operational Research, Elsevier, vol. 195(3), pages 662-675, June.
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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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