Presenting a model to determine the treatment of women with breast cancer in iran using data mining algorithms

Breast cancer is one of the most common types of cancer and the most common type of malignancy in women, which has recently had a growing trend. In patients with this disease, nutrition therapy is always one of the best and least risky treatments for breast cancer, but the most significant problem of the doctor is choosing the type of treatment for breast cancer. This article presents a method to help select the type of treatment regimen. For evaluating the proposed method, data from 683 cases breast cancer patients consist of 20 characteristics of each disease were used. After the pre processing and data preparation phase, a prediction model was proposed for nutritional therapy selection by decision tree optimization using the cuckoo algorithm. In this study, it represents that the use of the cuckoo optimization algorithm can increase the accuracy of the decision tree algorithm. The specificity and sensitivity of the proposed model were 94% and 91%, respectively. In this model, only 7% of the suggested nutrition types to patients are incorrect. For evaluation, using two algorithms, the nearest neighbor and the decision tree J48, the proposed algorithm examined, and the results show that the proposed algorithm has higher accuracy.