The prediction of recurrence of breast cancer by using of Technical Data mining

Introduction: The prediction of breast cancer recurrence is one of the most promising measures taken to develop data mining approaches; therefore, breast cancer detection is essential for better development. Since data mining can be effective in reducing the number of responses and false positives in decision making for treatment, we decided to carry out a study aimed at predicting the recurrence of breast cancer by using of data mining techniques.Methods: A total of 298 women with cancer who were followed for at least two years ,were included in the study by available sampling method. To predict the recurrence of cancer, decision support trees (C5.0) were used as a backup.Results: The results of investigation showed that accuracy of corresponding algorithms was C = 0.599 = 0.899 and SVM = 0.92.Conclusion: Given that the accuracy of data mining in the present study is very high in discovery and extraction of new knowledge from past data, its use is recommended.

Keywords:

Relapse , Breast Cancer , Data Mining