Artificial intelligence in mobile health applications: A comprehensive review of its role in diabetes care

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Authors: Wen-Jie Li, Lin-Ze Li
Cited by: 0
References: 52

Abstract

This review explores the integration of artificial intelligence (AI) in mobile health applications for diabetes care. It focuses on key AI methodologies - machine learning, deep learning, and natural language processing - and their roles in glucose monitoring, personalized self-management, risk prediction, and clinical decision support. Drawing on recent literature (2018-2024), the study outlines the benefits of AI in improving accuracy, engagement, and precision in diabetes treatment. Challenges such as data privacy, algorithmic bias, and regulatory barriers are also examined. A new section discusses when AI technologies may become burdensome, especially in low-resource settings or for users with limited digital literacy. The review concludes with directions for enhancing model explainability and integrating AI with wearable and Internet of Things devices, emphasizing the need for ethical and equitable implementation in future diabetes management strategies.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Mobile Health and mHealth Applications Artificial Intelligence in Healthcare

Publication details

Journal / source
World Journal of Methodology
Volume
16
Issue
1
Pages
107488–107488
Publication date
10 February 2026
Language
EN