Artificial Intelligence to Diagnose Complications of Diabetes.

Journal: Journal of diabetes science and technology
PMID: 39578435

Abstract

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.

Authors

  • Alessandra T Ayers
    Diabetes Technology Society, Burlingame, CA, USA.
  • Cindy N Ho
    Diabetes Technology Society, Burlingame, CA, USA.
  • David Kerr
    1 Sansum Diabetes Research Institute, Santa Barbara, CA, USA.
  • Simon Lebech Cichosz
    Department of Health Science and Technology, Aalborg University, Aalborg, Denmark.
  • Nestoras Mathioudakis
    School of Medicine, Johns Hopkins University, Baltimore, MD, USA.
  • Michelle Wang
    Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, California, USA.
  • Bijan Najafi
    Interdisciplinary Consortium on Advanced Motion Performance Lab (iCAMP), Department of Surgery, Baylor College of Medicine, Houston, TX, United States.
  • Sun-Joon Moon
    Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, School of Medicine, Sungkyunkwan University, Seoul, Republic of Korea.
  • Ambarish Pandey
    Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • David C Klonoff
    2 Mills-Peninsula Medical Center, San Mateo, CA, USA.

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