Integration of artificial intelligence and wearable technology in the management of diabetes and prediabetes
Raphael Fraser, Rebekah J. Walker, Jennifer A. Campbell, Obinna Ikechukwu Ekwunife, Leonard E. Egede
Abstract
Artificial intelligence and wearable technology are increasingly used in healthcare and hold significant potential for improving the management of diabetes. Wearable devices enable continuous monitoring and real-time data collection, supporting AI-driven personalized interventions. This systematic review evaluated peer-reviewed studies that examined the integration of AI and wearable technology in diabetes management, with a focus on clinical and self-management outcomes. Sixty studies were included following a review of over 5000 records. AI models paired with wearable devices showed promise in glycemic monitoring, adaptive insulin management, and predicting diabetes-related events. Continuous glucose monitors and other wearables also enhanced self-management and informed clinical decision-making. However, key challenges persist, including limited demographic diversity, variable data quality, a lack of standardized benchmarks for evaluating AI performance, and limited interpretability of complex models. Future research should prioritize improving model transparency, addressing demographic disparities, and establishing clear benchmarks to support equitable and effective implementation in diabetes care.