A Review on Data Mining Techniques for Prediction of Breast Cancer Recurrence

Authors

  • R.S.PadmaPriya Assistant Professor, Department of Computer Technology, Dr.N.G.P Arts and Science College, Coimbatore, INDIA
  • P.Senthil Vadivu Head of Department, Department of Computer Applications, Hindusthan College of Arts and Science, Coimbatore, INDIA

DOI:

https://doi.org/10.31033/ijemr.9.3.06

Keywords:

Association Rules, Classification, Decision Trees, Prediction, Recurrence

Abstract

The most common type of cancer in women worldwide is the Breast Cancer. Breast cancer may be detected early using Mammograms, probably before it's spread. Recurrent breast cancer could occur months or years after initial treatment. The cancer could return within the same place because the original cancer (local recurrence), or it may spread to different areas of your body (distant recurrence). Early stage treatment is done not only to cure breast cancer however additionally facilitate in preventing its repetition/recurrence. Data mining algorithms provide assistance in predicting the early-stage breast cancer that continually has been difficult analysis drawback. The projected analysis can establish the most effective algorithm that predicts the recurrence of the breast cancer and improve the accuracy the algorithms. Large information like Clump, Classification, Association Rules, Prediction and Neural Networks, Decision Trees can be analyzed using data mining applications and techniques.

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Published

2019-06-29

How to Cite

R.S.PadmaPriya, & P.Senthil Vadivu. (2019). A Review on Data Mining Techniques for Prediction of Breast Cancer Recurrence. International Journal of Engineering and Management Research, 9(3), 142–146. https://doi.org/10.31033/ijemr.9.3.06

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Articles