Advances in Breast Cancer Detection Techniques: A Comprehensive Survey

Abstract

Breast cancer is an old disease, but it has significantly spread in the past few periods, which led to the intervention of computer vision to solve the problem of classification and increase the accuracy of diagnosis to help doctors and radiologists. The computer task was not easy at first, but with artificial intelligence, the concept changed. There are several studies in this regard, from which we chose 27 modern studies from the year 2019 to the year 2023 in various ways to come out with results that are the focus of a new start in the classification. This review collected different machine learning methods, deep learning methods, and CNN structures. Through this study, deep learning shows its superiority over other techniques. The convolutional neural network is considered one of the most important techniques that is characterized by high accuracy in classifying medical images.

    This study comprehensively reviews various machine learning and deep learning techniques for breast cancer detection. It also shows that deep learning (CNN) technology is the best in giving accurate classification results. The choice of learning algorithm should have high accuracy if applied to medical images because the result is relevant to the patient's life which should be taken into consideration in the design phase.