Utilizing Artificial Intelligence Among Patients With Diabetes: A Systematic Review and Meta-Analysis

Area of Science:

• Medical Informatics
• Artificial Intelligence in Healthcare
• Public Health

Background:

• Diabetes mellitus, marked by blood glucose dysregulation, presents global health challenges.
• Effective diabetes management strategies are crucial to mitigate associated morbidity and mortality.
• Emerging health technologies, including AI, offer potential solutions for improved patient outcomes.

Purpose of the Study:

• To systematically review and meta-analyze the effectiveness of artificial intelligence (AI) in managing diabetes mellitus.
• To evaluate AI's role in early symptom detection and personalized management of diabetic patients.
• To assess AI applications against standard treatments and other machine learning models.

Main Methods:

• Systematic review and meta-analysis adhering to PRISMA guidelines.
• Searched six databases (Web of Science, Google Scholar, PubMed, Cochrane, EMBASE, MEDLINE) for studies from January 2019 to February 2024.
• Analyzed data using keywords related to AI, diabetes management, and health informatics.

Main Results:

• AI models demonstrated a trend towards better symptom prevalence management compared to standard care (RR 0.98).
• Sub-group analyses indicated AI favored symptom detection (RR 0.97) and management (RR 0.97).
• Consistent outcomes favored AI interventions across analyzed studies, with minimal heterogeneity (I² = 0%).

Conclusions:

• AI holds significant potential for enhancing diabetes care through early detection and personalized recommendations.
• AI interventions appear effective in improving patient outcomes and optimizing treatment efficacy in diabetes management.
• Expanded use of AI in healthcare settings is advocated to revolutionize diabetes care and reduce health risks.