AUTOMATED MACHINE LEARNING CLASSIFICATION OF OPTICAL COHERENCE TOMOGRAPHY IMAGES OF RETINAL CONDITIONS USING GOOGLE CLOUD VERTEX ARTIFICIAL INTELLIGENCE
Our automated machine learning model accurately classifies optical coherence tomography images of retinal conditions, demonstrating performance comparable or superior to traditional ML methods. Its user-friendly design supports scalable AI-driven clinical integration.
Authors
- Nikhil K. Bommakanti (ORCID: https://orcid.org/0000-0001-5429-0670)
- Yoshihiro Yonekawa (ORCID: https://orcid.org/0000-0002-6847-7169)
- Ajay E. Kuriyan (ORCID: https://orcid.org/0000-0002-2824-3245)
- Elliott M. Sina (ORCID: https://orcid.org/0009-0004-8473-8965)
- Sidra Zafar (ORCID: https://orcid.org/0000-0002-3474-5516)
- J. A. Larrea Peña (ORCID: https://orcid.org/0000-0003-0405-9723)
Institutions
- Thomas Jefferson University (US)
- Thomas Jefferson University Hospital (US)
- Jefferson University Hospitals (US)
- Wills Eye Hospital (US)
Publication Details
- Journal
- Retina
- Published
- 2025-06-16
- DOI
- https://doi.org/10.1097/iae.0000000000004555
- Citations
- 3
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 4.08