Breast Cancer Diagnosis by Different Machine Learning Methods Using Blood Analysis Data




Breast cancer, Artificial Neural Network, Extreme Learning Machine, Support Vector Machine, K-Nearest Neighbors, Hyperparameter Optimization


Today, one of the most common types of cancer is breast cancer. It is crucial to prevent the propagation of malign cells to reduce the rate of cancer induced mortality. Cancer detection must be done as early as possible for this purpose. Machine Learning techniques are used to diagnose or predict the success of treatment in medicine. In this study, four different machine learning algorithms were used to early detection of breast cancer. The aim of this study is to process the results of routine blood analysis with different ML methods and to understand how effective this method is for detection. Methods used can be listed as Artificial Neural Network (ANN), standard Extreme Learning Machine (ELM), Support Vector Machine (SVM) and K-Nearest Neighbor (k-NN). Dataset used were taken from UCI library. In this dataset age, body mass index (BMI), glucose, insulin, homeostasis model assessment (HOMA), leptin, adiponectin, resistin and chemokine monocyte chemoattractant protein 1 (MCP1)   attributes were used. Parameters that have the best accuracy values were found by using four different Machine Learning techniques. For this purpose, hyperparameter optimization method was used. In the end, the results were compared and discussed.


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Author Biographies

Muhammet Fatih Aslan, Karamanoğlu Mehmetbey University

Engineering Faculty, Department of Electrical and Electronics Engineering

Yunus Celik, Karamanoğlu Mehmetbey University

Engineering Faculty, Department of Electrical and Electronics Engineering

Kadir Sabanci, Karamanoğlu Mehmetbey University

Engineering Faculty, Department of Electrical and Electronics Engineering

Akif Durdu, Konya Technical University

Engineering and Natural Sciences Faculty, Department of Electrical and Electronics Engineering


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How to Cite

Aslan, M. F., Celik, Y., Sabanci, K., & Durdu, A. (2018). Breast Cancer Diagnosis by Different Machine Learning Methods Using Blood Analysis Data. International Journal of Intelligent Systems and Applications in Engineering, 6(4), 289–293.



Research Article

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