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Predicting glaucoma development with longitudinal deep learning predictions from fundus photographs
PURPOSE: To assess whether longitudinal changes in a deep learning algorithm’s predictions of retinal nerve fiber layer (RNFL) thickness based on fundus photographs can predict future development of glaucomatous visual field defects. DESIGN: Retrospective cohort study METHODS: This study included 10...
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| Pubblicato in: | Am J Ophthalmol |
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| Autori principali: | , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2021
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8239478/ https://ncbi.nlm.nih.gov/pubmed/33422463 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.ajo.2020.12.031 |
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