Application of artificial intelligence in the prevention, diagnosis, and treatment of breast cancer

Abstract

Breast cancer has affected the lives of millions of people around the world, and millions of people die from it every year. Despite their widespread use, traditional methods of cancer prevention, diagnosis, and treatment still have shortcomings in reducing mortality and the consequences of this type of cancer. With the emergence of artificial intelligence and its integration with the field of medicine, a significant amount of these problems can be overcome. Various models of artificial intelligence levels, including machine learning, deep learning, and neural networks, have been developed for use in the prevention, diagnosis, and treatment of breast cancer. In many cases, with their high speed and accuracy, they have played a complementary role alongside medical diagnoses and have led to remarkable advances in the field of prevention, diagnosis, and treatment of breast cancer. In addition to the many advantages of using artificial intelligence, existing concerns and disadvantages of using this tool must also be considered in order to make the most of this complex and, at the same time, useful technology. In this study, we will take a comprehensive look at the advantages, disadvantages, and peripheral aspects of using artificial intelligence in the field of breast cancer.