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Automated Identification of Referable Retinal Pathology in Teleophthalmology Setting
PURPOSE: This study aims to meet a growing need for a fully automated, learning-based interpretation tool for retinal images obtained remotely (e.g. teleophthalmology) through different imaging modalities that may include imperfect (uninterpretable) images. METHODS: A retrospective study of 1148 opt...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
The Association for Research in Vision and Ophthalmology
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8161696/ https://www.ncbi.nlm.nih.gov/pubmed/34036304 http://dx.doi.org/10.1167/tvst.10.6.30 |