Accessibility settings

This paper is in the following e-collection/theme issue:

Implementation Report (135) General Original Articles (3291) Letters to the Editor (397) Epublishing and Open Access (154)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67529, first published .
Eye exam in progress with ophthalmologist using slit lamp and laptop.

Real-World Evaluation of AI-Driven Diabetic Retinopathy Screening in Public Health Settings: Validation and Implementation Study

Real-World Evaluation of AI-Driven Diabetic Retinopathy Screening in Public Health Settings: Validation and Implementation Study

Authors of this article:

Mona Duggal1, 2 Author Orcid Image ;   Anshul Chauhan2 Author Orcid Image ;   Vishali Gupta2 Author Orcid Image ;   Ankita Kankaria3 Author Orcid Image ;   Deepmala Budhija2 Author Orcid Image ;   Priyanka Verma2 Author Orcid Image ;   Vaibhav Miglani2 Author Orcid Image ;   Preeti Syal4 Author Orcid Image ;   Gagandeep Kaur2 Author Orcid Image ;   Lakshay Kumar2 Author Orcid Image ;   Naveen Mutyala2 Author Orcid Image ;   Rishabh Bezbaruah4 Author Orcid Image ;   Nayanshi Sood5 Author Orcid Image ;   Ashleigh Kernohan6 Author Orcid Image ;   Geeta Menon7 Author Orcid Image ;   Luke Vale6 Author Orcid Image
Article Authors Cited by (16) Tweetations (2) Metrics

Journals

  1. Olivero Díaz L, Cárdenas Zambrano R, Ceja Casillas M, Guerrero Muñoz L, Restrepo Gómez J, Paloma Meza J, Luján Borjas J, Jaimes Hernández I. Terapia génica y cribado basado en IA en el futuro de la oftalmología. Multidisciplinary Journal of Sciences, Discoveries, and Society 2025;2(5) View
  2. Olivero Díaz L, Cárdenas Zambrano R, Ceja Casillas M, Guerrero Muñoz L, Restrepo Gómez J, Paloma Meza J, Luján Borjas J, Jaimes Hernández I. Terapia génica y cribado basado en IA en el futuro de la oftalmología. Multidisciplinary Journal of Sciences, Discoveries, and Society 2025;2(5):1 View
  3. Makhachev D, Musapirov I, Magomedova M, Abakarov M, Ametov D. Artificial intelligence in diabetology: systematizing clinical evidence and prospects for implementation. International journal of Innovative Medicine 2025;(2):4 View
  4. 李 银. Research Status of Diabetic Retinopathy Prediction Models: From Traditional Risk Factors to Artificial Intelligence. Journal of Clinical Personalized Medicine 2026;05(01):332 View
  5. Torres-Costa S, Machado S, Barbosa G, Carvalho E, Guerra A, Ramião N, Penas S, Parente M, Falcão M. Artificial intelligence in retinal vein occlusion: Current applications, challenges, and future directions. Survey of Ophthalmology 2026 View
  6. Miller M, Hsu D, Tailor P, Starr M. The evolving role of artificial intelligence in ophthalmology: basic science, translation, and clinical integration. Current Opinion in Ophthalmology 2026;37(5):367 View
  7. Jayaswal R, Chanu T, Kapani V, Pankaj P, Kant R. From benchmark accuracy to implementation equity: deploying diabetic retinopathy AI for scalable screening systems. International Journal of Diabetes in Developing Countries 2026 View
  8. Irlik K, Kwiendacz H, Wylęgała A, Bolek B, Gut-Misiaga M, Gil A, Piaśnik J, Jochemczyk J, Gryń I, Wójcik W, Wybraniec O, Łata J, Głuszko K, Miękina J, Jurek D, Niezgoda M, Ignacy P, Szromek-Białek P, Gumprecht J, Alam U, Lip G, Nabrdalik K. Diagnostic Accuracy of Artificial Intelligence-based Automated Detection of Diabetic Retinopathy in Routine Care Using Nonmydriatic Fundus Images: The Silesia Diabetes–Heart Project. Clinical Therapeutics 2026 View
  9. Zeppieri M, Capobianco M, Visalli F, Khouyyi M, Musa M, Avitabile A, Leandro I, Giglio R, Tognetto D, Gagliano C, D’Esposito F, Cappellani F. Artificial intelligence in ophthalmology: From diagnostic accuracy to clinical application. World Journal of Methodology 2026;16(3) View
  10. Sharma K, Shah K, Raman R. Teleophthalmology for Retinal Disease Screening and Referral in Low- and Middle-Income Countries: A Case Overview of India. International Ophthalmology 2026;46(1) View
  11. Sheng Q, Dong Q, Wu S, Liang W. ORDER-DR: external validation of severity grading and referable-risk stratification from fundus images. Frontiers in Endocrinology 2026;17 View
  12. Ali U, Imam A, Apong R. Leading Towards a Translation Readiness Framework: A Systematic Review of Deep Learning Approaches for Eye Disease Diagnosis. Diagnostics 2026;16(16):2500 View
  13. Zhou Y, Cen L. Nailfold capillaroscopy in diabetic retinopathy: microvascular insights, clinical value, and translational challenges — a narrative review. Frontiers in Endocrinology 2026;17 View
  14. Jung S, Han S, Yi E, Seo W, Kang Y, Park S, Cha J. Bridging primary care with artificial intelligence: toward a global 1.5-Tier Healthcare System. npj Health Systems 2026;3(1) View
  15. Jebaseeli T, Selvarathi M, Brindha D, David D, Juliet S, Angelin P. Wavelet Packet-Based Feature Extraction with Multivariate Kernel Sparse Extreme Learning Machine and DenseNet-264 for Diabetic Retinopathy Prediction. Sensing and Imaging 2026;27(1) View
  16. He Y, Li D, Li D, Ma Y, Huang W. Artificial intelligence-driven diabetic retinopathy research: mapping the evolution, coupling, and global collaboration landscape (1996-2026). Frontiers in Endocrinology 2026;17 View