Artificial Intelligence Enabled Lifestyle Medicine in Diabetes Care: A Narrative Review

Objective: To examine the applications of artificial intelligence (AI) in lifestyle medicine focused on diabetes care as a narrative review. Methods: Relevant keywords were identified and searched using PubMed to find relevant studies on AI in diabetes lifestyle management. Results: AI applications in diabetes care were divided into four primary categories: 1- predictive models for diabetes risk and complications, which can utilize random forest and deep learning, demonstrating high accuracy rates (>80%); 2- personalized lifestyle recommendations, which can utilize clustering techniques and causal forest analysis to adapt interventions, leading to enhanced glycemic control and weight reduction; 3- remote monitoring and self-management tools, which can utilize digital twin technology and machine learning for behavior modeling, showing improved patient adherence and clinical results; and 4- clinical decision support systems, which assess various data sources for enhanced diagnosis and treatment suggestions. Conclusion: AI technologies show significant potential in improving diabetes care through multiple modalities that offer scalable cost-effective solutions, improved patient outcomes, and more efficient resource distribution.