ArticleFrontiers in public health2026
Application study of an artificial intelligence and big data-based personalized chronic disease management model for diabetes patients.
Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Nurses' Roles in Supporting Digital Engagement and Self-Management in Adults with Type 2 Diabetes: A Scoping Review.Nursing reports (Pavia, Italy) · 2026Review
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Authors and funding
4 authors.
Funding
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Abstract
Background: To evaluate the real-world effectiveness of an artificial intelligence (AI) and big data-driven personalized chronic disease management model for type 2 diabetes mellitus (T2DM) patients, compared to conventional nurse-led management, and to identify factors associated with successful glycemic control within the personalized model. Methods: A retrospective cohort study was conducted involving 280 T2DM patients discharged from a single hospital between January 2019 and December 2024. Patients were divided into a conventional management group ( Results: At 6 months, the personalized management group demonstrated significantly better glycemic control (FBG: 6.79 ± 0.72 vs. 7.03 ± 0.89 mmol/L, Conclusion: The AI and big data-driven personalized management model significantly improved glycemic control, self-care behaviors, and quality of life in T2DM patients over conventional care within 6 months. Success within the model is influenced by behavioral and biological factors, alongside alcohol consumption. This approach demonstrates promise for enhancing diabetes care.
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