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UNSUPERVISED LEARNING WITH INDEPENDENT COMPONENT ANALYSIS CAN IDENTIFY PATTERNS OF GLAUCOMATOUS VISUAL FIELD DEFECTS

PURPOSE: We previously reported the use of clustering by unsupervised learning with machine learning classifiers to segment clusters of patterns in standard automated perimetry (SAP) for glaucoma. In this study, the process of unsupervised learning by independent component analysis decomposed SAP fi...

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Autore principale: Goldbaum, Michael Henry
Natura: Artigo
Lingua:Inglês
Pubblicazione: The American Ophthalmological Society 2005
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Accesso online:https://ncbi.nlm.nih.gov/pmc/articles/PMC1447578/
https://ncbi.nlm.nih.gov/pubmed/17057807
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