Artificial intelligence is currently capable of imitating clinical reasoning in order to make a diagnosis, in particular that of breast cancer. This is possible, thanks to the exponential increase in medical images. Indeed, artificial intelligence systems are used to assist doctors and not replace them. Breast cancer is a cancerous tumor that can invade and destroy nearby tissue. Therefore, early and reliable detection of this disease is a great asset for the medical field. Some people use medical imaging techniques to diagnose this disease. Given the drawbacks of these techniques, diagnostic errors of doctors related to fatigue or inexperience, this work consists of showing how artificial intelligence methods, in particular artificial neural networks (ANN), deep learning (DL), support vector machines (SVM), expert systems, fuzzy logic can be applied on breast imaging, with the aim of improving the detection of this global scourge. Finally, the proposed system is composed of two (2) essential steps: the tumor detection phase and the diagnostic phase allowing the latter to decide whether the tumor is benign or malignant
