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rdf:type |
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lifeskim:mentions |
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pubmed:issue |
11
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pubmed:dateCreated |
2009-10-6
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pubmed:abstractText |
Perimetry remains one of the main diagnostic tools in glaucoma, and it is usually used in conjunction with evaluation of the optic nerve. This study assesses the capability of automatic pattern recognition methods, and in particular the support vector machines (SVM), to provide a valid clinical diagnosis classification of glaucoma based solely upon perimetry data.
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pubmed:grant |
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pubmed:language |
eng
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pubmed:journal |
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pubmed:citationSubset |
IM
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pubmed:status |
MEDLINE
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pubmed:month |
Nov
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pubmed:issn |
1435-702X
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pubmed:author |
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pubmed:issnType |
Electronic
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pubmed:volume |
247
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
1517-30
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pubmed:dateRevised |
2010-11-18
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pubmed:meshHeading |
pubmed-meshheading:19579030-Aged,
pubmed-meshheading:19579030-Algorithms,
pubmed-meshheading:19579030-Glaucoma,
pubmed-meshheading:19579030-Humans,
pubmed-meshheading:19579030-Image Interpretation, Computer-Assisted,
pubmed-meshheading:19579030-Intraocular Pressure,
pubmed-meshheading:19579030-Middle Aged,
pubmed-meshheading:19579030-Ocular Hypertension,
pubmed-meshheading:19579030-Pattern Recognition, Automated,
pubmed-meshheading:19579030-Probability,
pubmed-meshheading:19579030-Visual Field Tests,
pubmed-meshheading:19579030-Visual Fields
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pubmed:year |
2009
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pubmed:articleTitle |
Glaucoma detection and evaluation through pattern recognition in standard automated perimetry data.
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pubmed:affiliation |
BioFormatix, Inc, San Diego, CA, USA. dariusz@bioformatix.com
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pubmed:publicationType |
Journal Article,
Research Support, N.I.H., Extramural
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