Abstract
Background
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.
Objectives
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.
Key Findings
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.
Conclusions
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.
Keywords
artificial intelligence - diabetes - Ramadan fasting - glycemic control - hypoglycemia
- closed-loop systems - predictive analytics - culturally competent care
