Elnaz Khodadadi - Department of Computer Engineering, Shahr Qods Branch, Islamic Azad University, Tehran, Iran
Seyed Mahdi Jameii - Department of Computer Engineering, Shahr Qods Branch, Islamic Azad University, Tehran, Iran

Breast cancer is the most common cancer among women. Prediction of breast cancer recurrence is the most vital element for its successful treatment. Breast cancer recurrence can appear every time. Developed data mining techniques can be used for finding models and hidden relations. Review of data mining methods applications for developing prediction models for recurrence of breast cancer is the purpose of this paper. Three algorithms such as: decision trees (DTs) , support vector machines (SVMs) and artificial neural networks (ANNs) are investigated in this paper. The predictive models discussed here are based on various supervised machine learning (ML) techniques as well as on different input features and data samples. Suggested techniques results reached to acceptable results on different database

Breast Cancer Recurrence, Data Mining, Decision Tree, Artificial Neural Network, Support Vector Machine