DIAGNOSTIC PERFORMANCE OF MACHINE LEARNING TECHNOLOGY USING OPTICAL COHERENCE TOMOGRAPHIC IMAGE IN RETINAL DISEASES PRESENTED WITH SUBRETINAL FLUID
The authors introduced a new aspect of developing a machine learning model to differentiate among three major retinal diseases presented with subretinal fluid from OCT images. The use of one-line across fovea OCT images combined with infrared photograph showed the highest diagnostic performance because of the possible imaging biomarkers.
Authors
- Pitchaya Wiratchotisatian (ORCID: https://orcid.org/0000-0002-7482-1229)
- Sarun Paisarnsrisomsuk
- Wipada Laovirojjanakul (ORCID: https://orcid.org/0000-0002-9290-3156)
- Kwankhao Tangprasert
- Panita Khakhai
Institutions
- Khon Kaen University (TH)
- Eye Center (SA)
Publication Details
- Journal
- Retina
- Published
- 2025-10-27
- DOI
- https://doi.org/10.1097/iae.0000000000004708
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00