ISI Report

Autoimmune diseases are a group of disorders that arise when the immune system attacks the body's own cells. The diagnosis of autoimmune diseases often involves complex and time-consuming processes that require the integration of multiple sources of information. Network-on-Chip (NoC) is a promising technology for the development of biomedical systems. Game theory provides a framework for modeling decision-making processes and has been used to improve the efficiency and accuracy of diagnosis. However, the use of game theory in the context of NoC for autoimmune disease diagnosis has not been explored. This article proposes a game theory-based approach for autoimmune disease diagnosis using NoC. The literature review examines the current state of autoimmune disease diagnosis, the challenges faced by NoC, and the potential benefits of game theory. The research methodology involves the development of a game theory-based approach for autoimmune disease diagnosis using NoC. The results show that the proposed approach can improve the efficiency and accuracy of autoimmune disease diagnosis. The conclusion discusses the implications of these findings for future research and the potential for game theory-based approaches to improve diagnosis in other healthcare domains.