Abstract: World Journal of Diabetes Research and Practice

Abstract:
Diabetes prevention and treatment are being revolutionized by AI and ML, which improve real-time management, tailored care, and early detection. In order to estimate the risk of diabetes and customize treatment regimens for each patient, AI and ML algorithms evaluate large, complicated datasets, such as data from continuous glucose monitoring and electronic health records. These devices provide dynamic, data-driven suggestions that optimize insulin dose and improve glycaemic control. Additionally, by locating new therapeutic targets, AI-driven research expedites the drug discovery process. Notwithstanding their potential, issues including algorithmic bias, data privacy, and integration with current healthcare systems need to be addressed. In addition to addressing the ongoing problems and potential for future research and development, this abstract investigates how AI and ML are transforming the future of diabetes care. It emphasizes the transformative impact of these technologies on managing and preventing diabetes.