Abstract

The management of diabetes mellitus, a chronic and complex metabolic disorder, demands highly individualized care to prevent complications and improve patient outcomes. Traditional treatment methods often fall short in addressing the dynamic and personalized needs of patients, leading to suboptimal glycemic control. Artificial Intelligence (AI), particularly predictive modeling, offers a transformative approach by leveraging vast amounts of data to anticipate and respond to individual variations in glucose levels. This article explores the integration of AI in diabetes management, focusing on its capability to predict blood glucose trends, personalize insulin dosing, recommend lifestyle modifications, and enhance patient engagement. Current applications of AI in diabetes care demonstrate significant improvements in glycemic control and patient adherence, while also enabling early detection of complications. However, the implementation of AI-driven solutions faces challenges such as data privacy, algorithmic bias, and integration with clinical workflows. Addressing these challenges is crucial for the successful adoption of AI technologies. The future of AI in diabetes care is promising, with ongoing advancements aiming to refine predictive models and enhance their practical utility. By harnessing AI's potential, we can move towards a more proactive, personalized, and effective management of diabetes, ultimately improving the quality of life for millions of patients worldwide.