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

Authors :
R.S.PadmaPriya
P.Senthil Vadivu
R.S.PadmaPriya
P.Senthil Vadivu
Source :
International Journal of Engineering and Management Research; Vol. 9 No. 3 (2019): June Issue; 142-146; 2250-0758; 2394-6962
Publication Year :
2019

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.

Details

Database :
OAIster
Journal :
International Journal of Engineering and Management Research; Vol. 9 No. 3 (2019): June Issue; 142-146; 2250-0758; 2394-6962
Notes :
application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1325639393
Document Type :
Electronic Resource