Advancement in medical science and health care technology has won increased expected lifetime for people in the twenty-first century. To meet the expectation of health care quality from the public, artificial intelligence (AI) techniques such as rule-based expert systems, fuzzy expert systems, artificial neural networks, genetic algorithms, and hybrid intelligent systems are widely used in medical science and health care services. The main objective is to promote AI applications research to address both theoretical and practical aspects of intelligent medical information, knowledge, and their management. These objectives have to be addressed by closely examining the synergy and the complementary nature of both theoretical and practical solutions of knowledge management and system development of health care intelligent systems. Consequently, current fundamental research results have to be further developed before offering operational procedures for practical robust AI applications in the work process for decision making and knowledge management in the framework of health care level. The medical field has made great strides in medical image processing thanks to recent advancements in deep neural networks (DNNs) and other AI technologies that have found widespread usage in healthcare. A lot of current research is focused on developing automated systems that can evaluate photos and detect acute ailments, including brain tumors, breast cancer, bone fractures, and a host of others. This would greatly benefit medical practitioners. This extensive study summarizes the most current developments in medical imaging that have made use of DNNs. Along with the extensive literature evaluation, there is an overview of publicly available data sources and ideas for future study.