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

Abstract

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.