University of Lynchburg DMSc Doctoral Project Assignment Repository

University of Lynchburg DMSc Doctoral Project Assignment Repository


Family Health


Dr. Thomas Colletti



Purpose: The purpose of this article is to review the current applications of AI in diabetic management.

Method: A literature search was conducted utilizing PubMed, CINAHL, Access Medicine, Google Scholar, and The Cochrane Library. Terms used to guide the search strategy included: diabetic management, artificial intelligence, machine learning. Fifteen pertinent articles were retrieved, and they serve as the basis for this clinical review.

Results: AI experiments and studies for use in diabetic management are on the rise as the technology continues to advance. There is evidence that AI can serve as another tool for clinicians who manage diabetes.

Conclusion: Artificial intelligence is a rapidly growing area of study in the medical community. As the number of diabetic patients outgrows the available medical resources, AI will prove to be a beneficial aid to clinicians treating this chronic disease. This review demonstrates that AI can be utilized throughout the diabetic care continuum. AI can help patients and clinicians achieve better glycemic control through self-management applications as well as clinician based prediction tools, respectively. Further research will be required as new technologies are developed and applied to diabetic care.


Available when accessing via a campus IP address or logged in with a University of Lynchburg email address.

Off-campus users can also use 'Off-campus Download' button above for access.