Artificial intelligence has positively impacted several fields, such as agriculture, automotive, and many others. Recently and especially with the emergence ofCovid, this technology has been used extensively in the medical field. AI is composed of different subfields: the most popular ones are Machine Learning (ML) and Deep Learning (DL).
ML algorithms allow computers to learn autonomously from data to accomplish a particular task. However, for computer vision, these traditional techniques require human intervention for feature extraction. Thus, with the development of deep learning, this phase is realized automatically without any intervention. Its architecture is inspired by the human brain, allowing it to deal with the most complex problems.
Innovation in AI technologies continues to bring new automated applications that improve the medical field. In the medical field. Deep learning models such as CNN can analyze different types of X-rays and thus detect and classify several diseases like cancer and glaucoma. Convolutional neural networks (CNNs) dominate complex computer vision problems thanks to their flexible and sophisticated architecture. Nevertheless, this architecture needs to be optimized in order to achieve surprising and outstanding results. AI applications will help improve the quality of diagnosis by quickly and early detecting infectious and life-threatening diseases, recommending treatment as well as facilitating and assisting practitioners in decision-making.