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Abstract

Keywords

artificial intelligence (AI)continuous glucose monitoring (CGM)data interpretation ambulatory glucose profile (AGP)glycemic control machine learning (ML)patient-specific clinical validation time in range diabetes management personalized therapy metabolic decline health information integration AI-driven models hybrid approach insights expert opinions clinician judgment insulin adjustment pregnancy metrics

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References

Bergenstal

. Roadmap to the effective use of continuous glucose monitoring: innovation, investigation, and implementation. Diabetes Spectr. 2023;36(4):327-336. https://pubmed.ncbi.nlm.nih.gov/37982061/. Accessed April 15, 2025.

Nimri

Muller

Atlas

, et al. Comparison of insulin dose adjustments made by artificial intelligence-based decision support system to those made by physicians for patients with type 1 diabetes. Diabetes Technol Ther. 2022;24(9):646-653. https://pubmed.ncbi.nlm.nih.gov/35325567/. Accessed April 15, 2025.

Nimri

Muller

Krcma

, et al. Adjusting insulin doses in patients with type 1 diabetes who use insulin pump and continuous glucose monitoring: variations among experienced physicians in routine care. Diabetes Obes Metab. 2018;20(10):2421-2426. https://pubmed.ncbi.nlm.nih.gov/29885025/. Accessed April 15, 2025.

Enhancing Continuous Glucose Monitoring: The Role of AI in Supporting Ambulatory Glucose Profile Interpretation

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