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Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression
PURPOSE: To apply computational techniques to wide-angle swept-source optical coherence tomography (SS-OCT) images to identify novel, glaucoma-related structural features and improve detection of glaucoma and prediction of future glaucomatous progression. METHODS: Wide-angle SS-OCT, OCT circumpapill...
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| Publicat a: | Invest Ophthalmol Vis Sci |
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| Autors principals: | , , , , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
The Association for Research in Vision and Ophthalmology
2018
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5983908/ https://ncbi.nlm.nih.gov/pubmed/29860461 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1167/iovs.17-23387 |
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