چكيده به لاتين
Breast cancer is the most common cancer among women, which can recur after recovery, and many women die each year consequently. Early detection of the possibility of recurrence of breast cancer can both prevent additional costs during treatment and reduce mortality. In this study, data mining techniques have been used to analyze the data of patients with a history of breast cancer in order to predict the recurrence of cancer in these patients. In this study, different algorithms of classification technique have been used, and it has been shown that a random forest algorithm with 98.08% accuracy, 96.21% precision, 99.21% sensitivity, and 97.29% specificity is the best efficiency among the algorithms used to predict breast cancer recurrence prediction. Also, in this study, in order to identify the antecedents that have led to the recurrence of breast cancer, the Apriori algorithm of the technique of the association rules was used, and the rules between the antecedents and the consequent were extracted.
