A New Hybrid Method Based on Fuzzy Logic and SVM to Solve the Breast Cancer Diagnosis

Broad-type breast cancer is one of the most common cancers in women. In many cases, breast cancer is not diagnosed until it reaches an advanced stage. This result is related to the unfortunate statistics of the survival rate of people with breast cancer and that a tool is needed for the rapid diagnosis of breast cancer. Mammography has fulfilled this need. In recent years, a lot of research has been done on mammography images, so that cancerous masses can be diagnosed without the intervention of the diagnostician by using image processing methods and computer programming, etc., so that fatigue, lack of it prevents the accuracy and visual mistakes of the person. Various approaches have been proposed to diagnose breast cancer, and one of the most dynamic and best methods is the Machine Learning (ML) technique, which performs this task at a high speed. In this paper, a new method for breast cancer diagnosis by scaling Support Vector Machine (SVM) based on fuzzy logic is presented. The results of the experiments show that the accuracy and precision of the proposed method will be more optimal compared to other algorithms and the algorithm has been able to compete with the compared algorithms.

کلیدواژه ها:

Breast cancer ، Mammography ، Support Vector Machines ، Fuzzy Logic