Implementation of Artificial Intelligence–Based Diabetic Retinopathy Screening in a Tertiary Care Hospital in Quebec: Prospective Validation Study
Our study indicates that integrating a semiautomated AI system for DR screening demonstrates high sensitivity for detecting referable disease in a real-world setting. This system has the potential to improve screening efficiency and reduce costs at the CHUM, but more work is needed to validate it.
Authors
- Pearse A. Keane (ORCID: https://orcid.org/0000-0002-9239-745X)
- Danny Gauthier
- Karim Hammamji (ORCID: https://orcid.org/0000-0001-5893-9174)
- I. Hammana (ORCID: https://orcid.org/0000-0002-7944-9868)
- M Jetté
- Mona Harissi‐Dagher (ORCID: https://orcid.org/0000-0002-9865-0137)
- Andrée Boucher (ORCID: https://orcid.org/0000-0003-2625-0086)
- Fares Antaki (ORCID: https://orcid.org/0000-0001-6679-7276)
- Ariel Yuhan Ong (ORCID: https://orcid.org/0000-0001-9300-573X)
- Marc‐André Rhéaume
- Alfons Pomp
- C. Beauchemin (ORCID: https://orcid.org/0000-0002-5903-5430)
- Marie-Catherine Tessier
Institutions
- Moorfields Eye Hospital NHS Foundation Trust (GB)
- NIHR Moorfields Biomedical Research Centre (GB)
- Centre Hospitalier de l’Université de Montréal (CA)
- Oxford University Hospitals NHS Trust (GB)
- Moorfields Eye Hospital (GB)
- University College London (GB)
- Université de Montréal (CA)
Publication Details
- Journal
- JMIR Diabetes
- Published
- 2024-09-03
- DOI
- https://doi.org/10.2196/59867
- Citations
- 6
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 2.43