Using Unsupervised Learning with Independent Component Analysis to Identify Patterns of Glaucomatous Visual Field Defects

PURPOSE: Clustering by unsupervised learning with machine learning classifiers was shown to segment clusters of patterns in standard automated perimetry (SAP) for glaucoma in previous publications. In this study, unsupervised learning by independent component analysis decomposed SAP field patterns i...

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Detalhes bibliográficos
Main Authors: Goldbaum, Michael H., Sample, Pamela A., Zhang, Zuohua, Chan, Kwokleung, Hao, Jiucang, Lee, Te-Won, Boden, Catherine, Bowd, Christopher, Bourne, Rupert, Zangwill, Linda, Sejnowski, Terrence, Spinak, David, Weinreb, Robert N.
Formato: Artigo
Idioma:Inglês
Publicado em: 2005
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Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC1866286/
https://ncbi.nlm.nih.gov/pubmed/16186349
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1167/iovs.04-1167
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