Using unsupervised learning with variational bayesian mixture of factor analysis to identify patterns of glaucomatous visual field defects

Investigative Ophthalmology and Visual Science

Volumn 45, Issue 8, 2004, Pages 2596-2605

  Sample, Pamela A ^a   Chan, Kwokleung ^a   Boden, Catherine ^a   Lee, Te Won ^a   Blumenthal, Eytan Z ^b   Weinreb, Robert N ^a   Bernd, Antje ^a   Pascual, John ^a   Hao, Jiucang ^a   Sejnowski, Terrence ^c   Goldbaum, Michael H ^a,d  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF CALIFORNIA SAN DIEGO   (United States)

^c HADASSAH HEBREW UNIVERSITY MEDICAL CENTER   (Israel)

^d SALK INSTITUTE FOR BIOLOGICAL STUDIES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGE; ARTICLE; BAYES THEOREM; CONTROLLED STUDY; FACTORIAL ANALYSIS; GLAUCOMA; GLAUCOMATOUS OPTIC NEUROPATHY; HUMAN; LEARNING; MAJOR CLINICAL STUDY; OPTIC DISK; OPTIC NERVE DISEASE; PERIMETRY; PRIORITY JOURNAL; VISUAL FIELD; VISUAL FIELD DEFECT;

ALGORITHMS; BAYES THEOREM; GLAUCOMA; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; LEARNING; MIDDLE AGED; OPTIC NERVE DISEASES; PERIMETRY; VISION DISORDERS; VISUAL FIELDS;

EID: 3242892323     PISSN: 01460404     EISSN: None     Source Type: Journal    
DOI: 10.1167/iovs.03-0343     Document Type: Article

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