Multi-Agent System Applications in the Diagnosis of Diabetes: A Systematic Review

Abstract Diabetes prevalence is rising globally, demanding better management and treatment strategies. The use of artificial intelligence (AI), particularly Multi-Agent Systems (MAS), in healthcare is increasingly utilized. Multiple agents are used by MAS to gather information assist physicians and assist patients in managing their diabetes. This review article aims to explore the use of MAS in the treatment of diabetes. We looked for research on MAS and diabetes using the PRISMA guidelines, searching popular databases such as PubMed, IEEE Xplore, and ScienceDirect. We examined and evaluated studies that used MAS for diagnosis, treatment support, monitoring, and patient self-care after implementing inclusion and exclusion criteria. Our findings suggest that MAS can improve personalized treatment plans help patients stay engaged in their own care and improve the precision of diabetes diagnosis. However, there are still issues like data privacy system complexity and the need for real-world testing. This review shows how MAS can improve diabetes management and patient engagement. Keywords: Multi-Agent System, Diabetes, Artificial Intelligence, Diagnosis, Management. Published by: International Journal of Science,Engineering and Technology Access link: Multi-Agent System Applications in the Diagnosis of Diabetes: A Systematic Review