Abstract Ramadan fasting poses unique challenges for individuals with diabetes, particularly regarding glycemic control and hypoglycemia risk. Artificial intelligence (AI) technologies are emerging as tools to support safe and individualized diabetes management during fasting. To explore the current and potential roles of AI in diabetes care during Ramadan, with a focus on clinical applications, patient outcomes, provider training, and barriers to adoption. AI is integrated into diabetes care through automated insulin delivery systems and machine learning–based risk prediction models. These tools support real-time glucose monitoring, hypoglycemia prevention, and personalized care, especially for high-risk groups. Type 1 diabetes patients benefit from closed-loop systems, whereas type 2 diabetes patients primarily use AI for predictive analytics. Regional resources, digital literacy, cultural perceptions, and provider training influence adoption. Barriers include cost, regulatory gaps, and algorithmic limitations in diverse populations. AI technologies hold promises for enhancing safety and glycemic outcomes for individuals with diabetes during Ramadan. Their optimal use depends on context-specific strategies, including culturally sensitive education, equitable access, and comprehensive training for providers. Further validation and customization of AI tools for fasting populations are necessary to support the widespread and effective implementation of these tools.
Salem Beshyah (Thu,) studied this question.