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

doi:10.5662/wjm.v16.i1.107488

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Mar 20, 2026 (publication date) through Feb 13, 2026

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World Journal of Methodology

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2222-0682

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

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World J Methodol. Mar 20, 2026; 16(1): 107488
Published online Mar 20, 2026. doi: 10.5662/wjm.v16.i1.107488

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

Wen-Jie Li, Lin-Ze Li

Wen-Jie Li, School of Art Design and Media, Guangzhou Xinhua University, Guangzhou 510520, Guangdong Province, China

Lin-Ze Li, School of the Arts, Universiti Sains Malaysia, Penang 11800, Malaysia

Author contributions: Li WJ was mainly responsible for drafting and structuring the manuscript, including the initial composition and integration of content, and played a key role in refining and editing the manuscript; Li LZ completed the systematic collection and organization of relevant literature, as well as revision of the manuscript, to ensure its academic rigor and coherence; and all authors thoroughly reviewed and endorsed the final manuscript.

Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.

Corresponding author: Lin-Ze Li, PhD, School of the Arts, Universiti Sains Malaysia, Chancellory, Level 1, Building E42, Penang 11800, Malaysia. lilinze@student.usm.my

Received: March 25, 2025
Revised: May 10, 2025
Accepted: August 5, 2025
Published online: March 20, 2026
Processing time: 323 Days and 1.2 Hours

Core Tip

Core Tip: This review highlights the transformative role of artificial intelligence in mobile health applications for diabetes care. It synthesizes recent advances in machine learning, deep learning, and natural language processing, examining their use in glucose monitoring, personalized interventions, and clinical decision support. The review also discusses ethical challenges, data privacy, and situations where artificial intelligence may become burdensome. By bridging technology and practice, this study offers insights into building more equitable, efficient, and patient-centered diabetes management systems.