Use of a Convolutional Neural Network to Predict the Response of Diabetic Macular Edema to Intravitreal Anti-VEGF Treatment: A Pilot Study
The results of this study demonstrate the potential of a CNN to predict the response of treatment-naïve DME to a single injection of anti-VEGF therapy. NOTE: Publication of this article is sponsored by the American Ophthalmological Society.
Authors
- Daniel B. Russakoff (ORCID: https://orcid.org/0000-0002-5713-1242)
- Jihad S. Obeid (ORCID: https://orcid.org/0000-0002-7193-7779)
- Gavin Baker (ORCID: https://orcid.org/0000-0001-9880-9665)
- Sally Tucker
- Jonathan D. Oakley (ORCID: https://orcid.org/0000-0003-2474-9609)
- Joseph Luvisi (ORCID: https://orcid.org/0000-0002-5469-4998)
- Emil Anthony T. Say (ORCID: https://orcid.org/0000-0002-2755-6274)
- Jeffrey P. Blice
- George N. Magrath (ORCID: https://orcid.org/0000-0002-2416-0821)
- Ashwath Jayagopal
- Alex Loayza
Institutions
- Medical University of South Carolina (US)
- Center for Human Genetics (US)
- Acceleron Pharma (United States) (US)
- A-T Society (GB)
- BD Technologie (United States) (US)
Publication Details
- Journal
- American Journal of Ophthalmology
- Published
- 2025-02-20
- DOI
- https://doi.org/10.1016/j.ajo.2025.02.017
- Citations
- 4
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 5.44
Funders
- Clemson University
- Medical University of South Carolina
- University of South Carolina
- National Institutes of Health
- National Center for Advancing Translational Sciences