Using Three Machine Learning Techniques for Predicting Breast Cancer Recurrence

Abstract

In order to predict the 2-year recurrence rate of breast cancer, we used ICBC dataset in the National Cancer Institute of Tehran for the years 1997-2008. The ICBC is responsible for collecting incidence and survival data from the participating registries, and disseminating these datasets for the purpose of conducting analytical research projects. This dataset contained population characteristics and included 22 input variables. Our cases were collected from the total number of 1189 women that were diagnosed breast cancer. We preprocessed the data to remove unsuitable cases. After using data cleansing and data preparation strategies, the final dataset was constructed. Finally, 547 cases were analyzed after 642 records were excluded because of missing data. Patients with breast cancer recurrence were followed-up