Assessing visual field clustering schemes using machine learning classifiers in standard perimetry

Investigative Ophthalmology and Visual Science

Volumn 48, Issue 12, 2007, Pages 5582-5590

  Boden, Catherine ^a   Chan, Kwokleung ^b,c   Sample, Pamela A ^a   Hao, Jiucang ^b   Lee, Te Wan ^b,c   Zangwill, Linda M ^a   Weinreb, Robert N ^a   Goldbaum, Michael H ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF CALIFORNIA SAN DIEGO   (United States)

^c SALK INSTITUTE FOR BIOLOGICAL STUDIES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; AGED; ARTICLE; CLUSTER ANALYSIS; CONTROLLED STUDY; DISCRIMINANT ANALYSIS; FEMALE; GLAUCOMA; HUMAN; KERNEL METHOD; MACHINE LEARNING; MAJOR CLINICAL STUDY; MALE; PERIMETRY; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE; VISUAL FIELD; VISUAL FIELD DEFECT; AREA UNDER THE CURVE; ARTIFICIAL INTELLIGENCE; COMPARATIVE STUDY; COMPUTER ASSISTED DIAGNOSIS; INTRAOCULAR PRESSURE; METHODOLOGY; MIDDLE AGED; OPTIC NERVE DISEASE; PHOTOGRAPHY; ROC CURVE; VISUAL DISORDER;

AGED; AREA UNDER CURVE; ARTIFICIAL INTELLIGENCE; DIAGNOSIS, COMPUTER-ASSISTED; DISCRIMINANT ANALYSIS; FEMALE; GLAUCOMA; HUMANS; INTRAOCULAR PRESSURE; MALE; MIDDLE AGED; OPTIC NERVE DISEASES; PERIMETRY; PHOTOGRAPHY; ROC CURVE; SENSITIVITY AND SPECIFICITY; VISION DISORDERS; VISUAL FIELDS;

EID: 38549104188     PISSN: 01460404     EISSN: None     Source Type: Journal    
DOI: 10.1167/iovs.06-0897     Document Type: Article

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