Predicting eyes at risk for rapid glaucoma progression based on an initial visual field test using machine learning

OBJECTIVE: To assess whether machine learning algorithms (MLA) can predict eyes that will undergo rapid glaucoma progression based on an initial visual field (VF) test. DESIGN: Retrospective analysis of longitudinal data. SUBJECTS: 175,786 VFs (22,925 initial VFs) from 14,217 patients who completed...

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Detalles Bibliográficos
Autores principales: Shuldiner, Scott R., Boland, Michael V., Ramulu, Pradeep Y., De Moraes, C. Gustavo, Elze, Tobias, Myers, Jonathan, Pasquale, Louis, Wellik, Sarah, Yohannan, Jithin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8051770/
https://www.ncbi.nlm.nih.gov/pubmed/33861775
http://dx.doi.org/10.1371/journal.pone.0249856

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8051770/
https://www.ncbi.nlm.nih.gov/pubmed/33861775
http://dx.doi.org/10.1371/journal.pone.0249856

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