Sensitivity and specificity of machine learning classifiers for glaucoma diagnosis using spectral domain oct and standard automated perimetry

Arquivos Brasileiros de Oftalmologia

Volumn 76, Issue 3, 2013, Pages 170-174

  Silva, Fabrício R ^a   Vidotti, Vanessa G ^a   Cremasco, Fernanda ^a   Dias, Marcelo ^b   Gomi, Edson S ^b   Costa, Vital P ^a  

^a UNIVERSITY OF CAMPINAS   (Brazil)

^b UNIVERSITY OF SÃO PAULO   (Brazil)

Author keywords

Diagnostic techniques; Glaucoma diagnosis; Ophthalmological classification; Optical coherence instrumentation; Sensitivity and specificity; Tomography

Indexed keywords

ADULT; AGED; ARTICLE; ARTIFICIAL INTELLIGENCE; CASE CONTROL STUDY; CHI SQUARE DISTRIBUTION; CROSS-SECTIONAL STUDY; EQUIPMENT; EVALUATION STUDY; FEMALE; GLAUCOMA; HUMAN; MALE; METHODOLOGY; MIDDLE AGED; OPTICAL COHERENCE TOMOGRAPHY; PERIMETRY; RECEIVER OPERATING CHARACTERISTIC; REFERENCE VALUE; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; VERY ELDERLY; VISUAL FIELD;

ADULT; AGED; AGED, 80 AND OVER; ARTIFICIAL INTELLIGENCE; CASE-CONTROL STUDIES; CHI-SQUARE DISTRIBUTION; CROSS-SECTIONAL STUDIES; FEMALE; GLAUCOMA; HUMANS; MALE; MIDDLE AGED; REFERENCE VALUES; REPRODUCIBILITY OF RESULTS; ROC CURVE; SENSITIVITY AND SPECIFICITY; TOMOGRAPHY, OPTICAL COHERENCE; VISUAL FIELD TESTS; VISUAL FIELDS;

EID: 84883735736     PISSN: 00042749     EISSN: 16782925     Source Type: Journal    
DOI: 10.1590/S0004-27492013000300008     Document Type: Article

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