The Role of Artificial Intelligence in Enhancing Insulin Recommendations and Therapy Outcomes
This is an incremental review that discusses improving insulin therapy outcomes for people with diabetes through AI advancements.
The paper addresses the need for better blood glucose management in diabetes by highlighting how AI, especially reinforcement learning, enhances insulin delivery systems for personalized dosing, though it notes ongoing challenges like data privacy and accessibility.
The growing worldwide incidence of diabetes requires more effective approaches for managing blood glucose levels. Insulin delivery systems have advanced significantly, with artificial intelligence (AI) playing a key role in improving their precision and adaptability. AI algorithms, particularly those based on reinforcement learning, allow for personalised insulin dosing by continuously adapting to an individual's responses. Despite these advancements, challenges such as data privacy, algorithm transparency, and accessibility still need to be addressed. Continued progress and validation in AI-driven insulin delivery systems promise to improve therapy outcomes further, offering people more effective and individualised management of their diabetes. This paper presents an overview of current strategies, key challenges, and future directions.