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

Diabetic Retinopathy (31) mHealth for Screening (489) Aging with Chronic Disease (560) Artificial Intelligence (5098) Artificial Intelligence in Diabetes Care and Prevention (118) Computer-Aided Diagnosis (449)

Published on in Vol 9 (2024)

This is a member publication of University College London (Jisc)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/59867, first published .
Extreme close-up of a human eye, showing iris detail and eyelashes

Implementation of Artificial Intelligence–Based Diabetic Retinopathy Screening in a Tertiary Care Hospital in Quebec: Prospective Validation Study

Implementation of Artificial Intelligence–Based Diabetic Retinopathy Screening in a Tertiary Care Hospital in Quebec: Prospective Validation Study

Authors of this article:

Fares Antaki1, 2, 3, 4, 5 Author Orcid Image ;   Imane Hammana6 Author Orcid Image ;   Marie-Catherine Tessier2 Author Orcid Image ;   Andrée Boucher7 Author Orcid Image ;   Maud Laurence David Jetté8 Author Orcid Image ;   Catherine Beauchemin9 Author Orcid Image ;   Karim Hammamji2, 3 Author Orcid Image ;   Ariel Yuhan Ong1, 5, 10 Author Orcid Image ;   Marc-André Rhéaume2, 3 Author Orcid Image ;   Danny Gauthier2, 3 Author Orcid Image ;   Mona Harissi-Dagher2, 3 Author Orcid Image ;   Pearse A Keane1, 5, 11 Author Orcid Image ;   Alfons Pomp6, 12 Author Orcid Image
Article Authors Cited by (11) Tweetations Metrics

Journals

  1. Soe M, Ge J, Aung K, La S, Tan A. The implementation of artificial intelligence driven diabetic retinopathy screening in a district hospital in Myanmar: a pilot study. AJO International 2025;2(3):100149 View
  2. Tappeiner C. Artificial Intelligence in Ophthalmology: Acceptance, Clinical Integration, and Educational Needs in Switzerland. Journal of Clinical Medicine 2025;14(17):6307 View
  3. Nada A, Ahmed Y, Hu J, Weidemann D, Gorman G, Lecea E, Sandokji I, Cha S, Shin S, Bani-Hani S, Mannemuddhu S, Ruebner R, Kakajiwala A, Raina R, George R, Elchaki R, Moritz M. AI-powered insights in pediatric nephrology: current applications and future opportunities. Pediatric Nephrology 2026;41(5):1275 View
  4. Tseng R, Ong L, Goh J, Chen Y, Chen T, Lum E, Tham Y. Prospective real-world implementation of deep learning systems in healthcare: a systematic review guided by implementation science. npj Digital Medicine 2026;9(1) View
  5. Chen Y, Koh K, Ho J, Yew S, Goh J, Lum E, Tham Y. Evaluation of a Community-Based AI-Assisted Visual Impairment Screening Model for Performance, Operational Efficiency, Acceptability, Feasibility, and Costs: Protocol for a 2-Arm Pragmatic Randomized Controlled Trial. JMIR Research Protocols 2026;15:e74164 View
  6. Zhou J, Hu C, Chen J, Liu J, Li X. Artificial Intelligence in Screening and Grading Diabetic Eye Diseases: A Systematic Review From Algorithms to Clinic. Diabetes, Obesity and Metabolism 2026;28(5):4286 View
  7. Luo Y, Bu D, Wu Y, Zhao Y. Artificial Intelligence in Medical Informatics: From Algorithms to Clinical Practice—A Survey. Journal of Computer Science and Technology 2026;41(1):447 View
  8. Madi M, Farr P, Bester D, Panos G. Diabetic Retinopathy Detection: AI Models and Approaches. Journal of Ophthalmology 2026;2026(1) View
  9. 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
  10. Alharbi M, Alharbi E, Alsalamah A, Asiri H, Beati N, AlAtawi R, Arafat A. Artificial Intelligence in Eye Disease: A Systematic Review of Screening, Diagnosis, Prognosis, Treatment-Response Prediction, and Clinical Decision Support. Journal of Clinical Medicine 2026;15(20):7957 View

Books/Policy Documents

  1. Capacho-Alfonso V, Soto-Durán D, Jimenez-Builes J. Health Technologies and Demographic Challenges. View