Using four common machine learning methods to classify breast cancer

Cancer is the second leading cause of death in the world. Among the types of cancer, breast canceris the most common disease of women worldwide,۳۰% of women’s cancers are included.Oureffort is to study and research breast tissue cancer cells using machine learning methods, whichare considered a subset of artificial intelligence.Machine learning techniques have great potential in diagnosing and classifying cancer and normalcellsMethods: In this study, ۱۲۰ patients with breast cancer were examined, all of whom underwentsurgery. ۶ characteristics were considered for each person and these characteristicswere examined using machine learning techniques. Decision tree, random forest and Support vectormachine are the methods that we used to check them. We attempt to measure the relationshipbetween these data.Result: In this research, support vector machine showed ۷۷% accuracy, decision tree ۸۲% andrandom forest showed ۶۰% accuracy. Among these techniques, the decision tree method wasmore powerful than others.Conclusion: To improve the accuracy of the methods used to predict cancer cells, increasingthe number of patients and combining different characteristics that affect cancerous cells is veryeffective.

کلیدواژه ها:

Artificial intelligence ، machine learning ، breast cancer ، prediction and early diagnosis