A Review of Classifications Techniques and computer aided used for Breast Cancer Detection

One of the most prevalent and deadly diseases in women is breast cancer due to the increasing incidence, many researchers have become interested in it in recent years. Due to the difficulty of distinguishing with high accuracy the infected and nonaffected breast tissue, computer-assisted diagnostic techniques were introduced, as the correct diagnosis requires the use of methods for extracting the distinctive characteristics of breast tissue. Pre-processing, features extraction, and classification are the three primary processes that make up the machine learning method for detecting breast cancer. Because it has a significant impact on the accuracy of the extracted system, as the methods used to extract the distinctive characteristics of breast tissue and thus affect the patient's life, so several methods were used. This research paper aims to study, analyze and compare the methods used to determine the characteristics of breast tissue for the purpose of accurate diagnosis of breast cancer.