Artificial Intelligence to Diagnose Complications of Diabetes.

Publisher: Sage Country of Publication: United States NLM ID: 101306166 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1932-2968 (Electronic) Linking ISSN: 19322968 NLM ISO Abbreviation: J Diabetes Sci Technol Subsets: MEDLINE

Publication: 2014- : Thousand Oaks, CA : Sage
Original Publication: Foster City, CA : Diabetes Technology Society

Artificial Intelligence* ; Diabetes Complications*/diagnosis; Humans

Artificial intelligence (AI) is increasingly being used to diagnose complications of diabetes. Artificial intelligence is technology that enables computers and machines to simulate human intelligence and solve complicated problems. In this article, we address current and likely future applications for AI to be applied to diabetes and its complications, including pharmacoadherence to therapy, diagnosis of hypoglycemia, diabetic eye disease, diabetic kidney diseases, diabetic neuropathy, diabetic foot ulcers, and heart failure in diabetes.Artificial intelligence is advantageous because it can handle large and complex datasets from a variety of sources. With each additional type of data incorporated into a clinical picture of a patient, the calculation becomes increasingly complex and specific. Artificial intelligence is the foundation of emerging medical technologies; it will power the future of diagnosing diabetes complications.
Competing Interests: Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: ATA is a consultant for Liom. CNH is a consultant for Liom. DK has received research support from Abbott Diabetes Care and consultancy fees from Perfood. SLC has received research support from i-SENS, Inc. NM has nothing to disclose. MW has nothing to disclose. BN is serving as a consultant for BioSensics LLC and Mölnlycke Health on projects unrelated to the scope of this paper. S-JM is a consultant for Abbott, Curestream, Daweoong, EOFlow, G2e, iSense, Medtronic, Novo Nordisk, and Sanofi. AP has received grant funding (to the institution) from Applied Therapeutics, Gilead Sciences, Ultromics, Myovista, and Roche; has served as a consultant for and/or received honoraria outside of the present study as an advisor/consultant for Tricog Health Inc, Lilly USA, Rivus; Cytokinetics, Roche Diagnostics, Sarfez Therapeutics, Edwards Lifesciences, Merck, Bayer, Novo Nordisk, Alleviant, Axon Therapies, and has received nonfinancial support from Pfizer and Merck. AP is also a consultant for Palomarin Inc with stocks compensation and has received research support from the National Institute on Aging GEMSSTAR Grant (1R03AG067960-01), the National Institute on Minority Health and Disparities (R01MD017529), and the National Institute of Heart, Lung, and Blood Institute (R21HL169708). DCK is a consultant for Afon, Embecta, Glucotrack, Lifecare, Novo, Samsung, Synchneuro and Thirdwayv.

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R01 MD017529 United States MD NIMHD NIH HHS; R03 AG067960 United States AG NIA NIH HHS; R21 HL169708 United States HL NHLBI NIH HHS

Keywords: artificial intelligence; complications; diabetes; diagnosis; machine learning

Date Created: 20241123 Date Completed: 20250101 Latest Revision: 20250104

20250104

PMC11688687

10.1177/19322968241287773

39578435