Bayesian machine learning classifiers for combining structural and functional measurements to classify healthy and glaucomatous eyes

Investigative Ophthalmology and Visual Science

Volumn 49, Issue 3, 2008, Pages 945-953

  Bowd, Christopher ^a   Hao, Jiucang ^b   Tavares, Ivan M ^a   Medeiros, Felipe A ^a   Zangwill, Linda M ^a   Lee, Te Won ^b,c   Sample, Pamela A ^a   Weinreb, Robert N ^a   Goldbaum, Michael H ^a,d  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF CALIFORNIA SAN DIEGO   (United States)

^c SALK INSTITUTE FOR BIOLOGICAL STUDIES   (United States)

^d VETERANS AFFAIRS MEDICAL CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; ARTICLE; BAYES THEOREM; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; GLAUCOMA; HUMAN; MACHINE LEARNING; MAJOR CLINICAL STUDY; MEASUREMENT; OPTICAL COHERENCE TOMOGRAPHY; PERIMETRY; PRIORITY JOURNAL; RELEVANCE VECTOR MACHINE; VISUAL FIELD; AGED; ALGORITHM; CROSS-SECTIONAL STUDY; MIDDLE AGED; NERVE FIBER; OCULOPLETHYSMOGRAPHY; OPEN ANGLE GLAUCOMA; OPTIC DISK; OPTIC NERVE DISEASE; PATHOLOGY; RETINA GANGLION CELL; ROC CURVE; VISUAL DISORDER;

ADULT; AGED; AGED, 80 AND OVER; ALGORITHMS; BAYES THEOREM; CROSS-SECTIONAL STUDIES; GLAUCOMA, OPEN-ANGLE; HUMANS; MIDDLE AGED; NERVE FIBERS; OPTIC DISK; OPTIC NERVE DISEASES; PERIMETRY; RETINAL GANGLION CELLS; ROC CURVE; TOMOGRAPHY, OPTICAL COHERENCE; TONOMETRY, OCULAR; VISION DISORDERS; VISUAL FIELDS;

EID: 41949089226     PISSN: 01460404     EISSN: 15525783     Source Type: Journal    
DOI: 10.1167/iovs.07-1083     Document Type: Article

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