@Article{cmes.2022.019782,
AUTHOR = {Nezihal Gokbulut, Evren Hincal, Hasan Besim, Bilgen Kaymakamzade},
TITLE = {Reducing the Range of Cancer Risk on BI-RADS 4 Subcategories via Mathematical Modelling},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {133},
YEAR = {2022},
NUMBER = {1},
PAGES = {93--109},
URL = {http://www.techscience.com/CMES/v133n1/48848},
ISSN = {1526-1506},
ABSTRACT = {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.},
DOI = {10.32604/cmes.2022.019782}
}