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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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| Autor principal: | |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
The American Ophthalmological Society
2005
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC1447578/ https://ncbi.nlm.nih.gov/pubmed/17057807 |
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