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CC BY 4.0 · Journal of Diabetes and Endocrine Practice
DOI: 10.1055/s-0045-1811513
Review Article

Artificial Intelligence for Diabetes Care during Ramadan Fasting: A Narrative Review

Salem A. Beshyah 
1   Department of Medicine, Bareen International Hospital, Abu Dhabi, United Arab Emirates
2   Department of Medicine, College of Medicine, Dubai Medical University, Dubai, United Arab Emirates
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Funding and Sponsorship None.
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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

Use of AI in Scientific Writing

During the composition of this review, the author used generative AI tools solely for literature discovery and drafting assistance. Specifically, Open Evidence was consulted on June 29, 2025. The author reviewed and edited all substantive content, assuming full accountability for the manuscript's intellectual integrity and originality.


Compliance with Ethical Principles

No ethical approval is required for narrative review articles.


Data Availability Statement

Not applicable.




Publikationsverlauf

Artikel online veröffentlicht:
21. August 2025

© 2025. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

Thieme Medical and Scientific Publishers Pvt. Ltd.
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