Health Technology/clinical-trials

Terminated Trial Analysis: NeoRetina AI Algorithm vs. Expert Ophthalmologist Grading for Diabetic Retinopathy Detection — Lessons for Clinicians

247 Health News Editorial

·

26 July 2026

·

4 min read

·clinical-trials

A Canadian prospective study at the Centre hospitalier de l'Université de Montréal evaluated the NeoRetina AI algorithm against specialist ophthalmologist grading for diabetic retinopathy and macular edema detection. The trial, which enrolled 24 participants before being terminated, reflects both the promise and the real-world challenges of validating AI-based retinal screening tools in clinical settings. Clinicians managing diabetic patients should monitor this evolving evidence base as scalable screening solutions remain an urgent unmet need.

Originally reported by ClinicalTrials.gov

References

  1. 1.Centre hospitalier de l'Université de Montréal (CHUM). (2021). The use of artificial intelligence in the early detection and the follow-up of diabetic retinopathy of diabetic patients followed at the CHUM: Evaluation of NeoRetina automated algorithm (DIAGNOS Inc.) (NCT04699864). ClinicalTrials.gov. https://clinicaltrials.gov/study/NCT04699864
  2. 2.Teo, Z. L., Tham, Y. C., Yu, M., Chee, M. L., Rim, T. H., Cheung, N., Bikbov, M. M., Wang, Y. X., Tang, Y., Lu, Y., Wong, I. Y., Ting, D. S. W., Tan, G. S. W., Wong, T. Y., & Cheung, C. Y. (2021). Global prevalence of diabetic retinopathy and projection of burden through 2045: Systematic review and meta-analysis. Ophthalmology, 128(11), 1580–1591. https://doi.org/10.1016/j.ophtha.2021.04.027
  3. 3.Ting, D. S. W., Cheung, C. Y. L., Lim, G., Tan, G. S. W., Quang, N. D., Gan, A., Hamzah, H., Garcia-Franco, R., San Yeo, I. Y., Lee, S. Y., Wong, E. Y. M., Sabanayagam, C., Baskaran, M., Ibrahim, F., Tan, N. C., Finkelstein, E. A., Lamoureux, E. L., Wong, I. Y., Bressler, N. M., … Wong, T. Y. (2017). Development and validation of a deep learning system for diabetic retinopathy and related eye diseases using retinal images from multiethnic populations with diabetes. JAMA, 318(22), 2211–2223. https://doi.org/10.1001/jama.2017.18152
  4. 4.Yau, J. W. Y., Rogers, S. L., Kawasaki, R., Lamoureux, E. L., Kowalski, J. W., Bek, T., Chen, S. J., Dekker, J. M., Fletcher, A., Grauslund, J., Haffner, S., Hamman, R. F., Ikram, M. K., Kayama, T., Klein, B. E. K., Klein, R., Krishnaiah, S., Mayurasakorn, K., O'Hare, J. P., … Wong, T. Y. (2012). Global prevalence and major risk factors of diabetic retinopathy. Diabetes Care, 35(3), 556–564. https://doi.org/10.2337/dc11-1909
  5. 5.Abràmoff, M. D., Lavin, P. T., Birch, M., Shah, N., & Folk, J. C. (2018). Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices. npj Digital Medicine, 1, Article 39. https://doi.org/10.1038/s41746-018-0040-6
  6. 6.Diabetic Retinopathy Clinical Research Network, Wells, J. A., Glassman, A. R., Ayala, A. R., Jampol, L. M., Aiello, L. P., Antoszyk, A. N., Arnold-Bush, B., Baker, C. W., Bressler, N. M., Browning, D. J., Elman, M. J., Ferris, F. L., Friedman, S. M., Melia, M., Pieramici, D. J., Sun, J. K., & Beck, R. W. (2015). Aflibercept, bevacizumab, or ranibizumab for diabetic macular edema. New England Journal of Medicine, 372(13), 1193–1203. https://doi.org/10.1056/NEJMoa1414264
Share:XLinkedIn
2

247 Health News Editorial

247 Health News is a medical intelligence platform delivering evidence-based research appraisals, clinical trial monitoring, and health technology news for healthcare professionals.

This content is for educational purposes for healthcare professionals only and does not constitute clinical advice. Clinical decisions should be based on individual patient assessment, current guidelines, and appropriate specialist consultation. Editorial Standards · Privacy Policy · Terms of Service