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A Deep Learning Algorithm for Classifying Diabetic Retinopathy Using Optical Coherence Tomography Angiography
PURPOSE: To develop an automated diabetic retinopathy (DR) staging system using optical coherence tomography angiography (OCTA) images with a convolutional neural network (CNN) and to verify the feasibility of the system. METHODS: In this retrospective cross-sectional study, a total of 918 data sets...
Autores principales: | Ryu, Gahyung, Lee, Kyungmin, Park, Donggeun, Kim, Inhye, Park, Sang Hyun, Sagong, Min |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Association for Research in Vision and Ophthalmology
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8899862/ https://www.ncbi.nlm.nih.gov/pubmed/35703566 http://dx.doi.org/10.1167/tvst.11.2.39 |
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