Artificial intelligence for early detection of diabetes mellitus complications via retinal imaging.

Journal: Journal of diabetes and metabolic disorders
Published Date: Apr 12, 2025

Abstract

BACKGROUND: Diabetes mellitus (DM) increases the risk of vascular complications, and retinal vasculature imaging serves as a valuable indicator of both microvascular and macrovascular health. Moreover, artificial intelligence (AI)-enabled systems developed for high-throughput detection of diabetic retinopathy (DR) using digitized retinal images have become clinically adopted. This study reviews AI applications using retinal images for DM-related complications, highlighting advancements beyond DR screening, diagnosis, and prognosis, and addresses implementation challenges, such as ethics, data privacy, equitable access, and explainability.

Authors

  • Navid Sobhi
    Nikookari Eye Center, Tabriz University of Medical Sciences, Tabriz, Iran.
  • Yasin Sadeghi-Bazargani
    Student Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran.
  • Majid Mirzaei
    Student Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran.
  • Mirsaeed Abdollahi
    Nikookari Eye Center, Tabriz University of Medical Sciences, Tabriz, Iran.
  • Ali Jafarizadeh
    Nikookari Eye Center, Tabriz University of Medical Sciences, Tabriz, Iran.
  • Siamak Pedrammehr
    Faculty of Design, Tabriz Islamic Art University, Tabriz, Iran.
  • Roohallah Alizadehsani
    Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Geelong, Australia.
  • Ru-San Tan
    National Heart Centre Singapore, Singapore, Singapore.
  • Sheikh Mohammed Shariful Islam
    Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, 3220, Australia.
  • U Rajendra Acharya
    School of Business (Information Systems), Faculty of Business, Education, Law & Arts, University of Southern Queensland, Darling Heights, Australia.

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