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

Saved in:
Bibliographic Details
Title: Artificial intelligence for early detection of diabetes mellitus complications via retinal imaging.
Authors: Sobhi N; Nikookari Eye Center, Tabriz University of Medical Sciences, Tabriz, Iran., Sadeghi-Bazargani Y; Student Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran., Mirzaei M; Student Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran., Abdollahi M; Nikookari Eye Center, Tabriz University of Medical Sciences, Tabriz, Iran., Jafarizadeh A; Nikookari Eye Center, Tabriz University of Medical Sciences, Tabriz, Iran., Pedrammehr S; Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, 75 Pigdons Rd, Waurn Ponds, VIC 3216 Australia.; Faculty of Design, Tabriz Islamic Art University, Tabriz, Iran., Alizadehsani R; Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, 75 Pigdons Rd, Waurn Ponds, VIC 3216 Australia., Tan RS; National Heart Centre Singapore, Singapore, Singapore.; Duke-NUS Medical School, Singapore, Singapore., Islam SMS; Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, VIC Australia.; Cardiovascular Division, The George Institute for Global Health, Newtown, Australia.; Sydney Medical School, University of Sydney, Camperdown, Australia., Acharya UR; School of Mathematics, Physics, and Computing, University of Southern Queensland, Springfield, QLD 4300 Australia.; Centre for Health Research, University of Southern Queensland, Springfield, Australia.
Source: Journal of diabetes and metabolic disorders [J Diabetes Metab Disord] 2025 Apr 12; Vol. 24 (1), pp. 104. Date of Electronic Publication: 2025 Apr 12 (Print Publication: 2025).
Publication Type: Journal Article; Review
Journal Info: Publisher: Springer International Publishing Country of Publication: Switzerland NLM ID: 101590741 Publication Model: eCollection Cited Medium: Print ISSN: 2251-6581 (Print) Linking ISSN: 22516581 NLM ISO Abbreviation: J Diabetes Metab Disord Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Full text is not displayed to guests.
Description
ISSN:2251-6581
DOI:10.1007/s40200-025-01596-7