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Reducing the Range of Cancer Risk on BI-RADS 4 Subcategories via Mathematical Modelling

Nezihal Gokbulut1,2, Evren Hincal1,2,*, Hasan Besim3, Bilgen Kaymakamzade1,2

1 Near East University, Faculty of Arts and Sciences, Nicosia, 99138, North Cyprus
2 Near East University, Mathematics Research Center, Nicosia, 99138, North Cyprus
3 Near East University, Faculty of Medicine, Nicosia, 99138, North Cyprus

* Corresponding Author: Evren Hincal. Email:

(This article belongs to this Special Issue: Mathematical Aspects of Computational Biology and Bioinformatics)

Computer Modeling in Engineering & Sciences 2022, 133(1), 93-109.


Breast Imaging Reporting and Data System, also known as BI-RADS is a universal system used by radiologists and doctors. It constructs a comprehensive language for the diagnosis of breast cancer. BI-RADS 4 category has a wide range of cancer risk since it is divided into 3 categories. Mathematical models play an important role in the diagnosis and treatment of cancer. In this study, data of 42 BI-RADS 4 patients taken from the Center for Breast Health, Near East University Hospital is utilized. Regarding the analysis, a mathematical model is constructed by dividing the population into 4 compartments. Sensitivity analysis is applied to the parameters with the desired outcome of a reduced range of cancer risk. Numerical simulations of the parameters are demonstrated. The results of the model have revealed that an increase in the lactation rate and early menopause have a negative correlation with the chance of being diagnosed with BI-RADS 4 whereas a positive correlation increase in age, the palpable mass, and family history is distinctive. Furthermore, the negative effects of smoking and late menopause on BI-RADS 4C diagnosis are vehemently outlined. Consequently, the model showed that the percentages of parameters play an important role in the diagnosis of BI-RADS 4 subcategories. All things considered, with the assistance of the most effective parameters, the range of cancer risks in BI-RADS 4 subcategories will decrease.


Cite This Article

Gokbulut, N., Hincal, E., Besim, H., Kaymakamzade, B. (2022). Reducing the Range of Cancer Risk on BI-RADS 4 Subcategories via Mathematical Modelling. CMES-Computer Modeling in Engineering & Sciences, 133(1), 93–109.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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