Enhancing the accuracy of breast cancer detection and determination of risk factor by using the backpropagation network theory and SVM: Machine learning

Abstract

According to the world health organization, every year, more than 8% of women suffer due to breast cancer, and 40% of women die in low-poverty regions. This entire work focuses on the algorithm to detect breast cancer. This algorithm improves the accuracy of the detection and the risk factor determination by using the backpropagation network (BPN) theory and the Support vector method (SVM). By the end of the entire work, the improved accuracy is up to 95% compared to other forms; this proposed method is proper when evaluating the patient report in the image format, like a scanning report.