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Volumn 174, Issue , 2017, Pages 95-103

Validating the Usefulness of the “Random Forests” Classifier to Diagnose Early Glaucoma With Optical Coherence Tomography

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; ALGORITHM; ARTICLE; CLASSIFIER; CONTROLLED STUDY; CROSS-SECTIONAL STUDY; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; EARLY DIAGNOSIS; FEMALE; HUMAN; INSTITUTIONAL CARE; MAJOR CLINICAL STUDY; MALE; MIDDLE AGED; OPEN ANGLE GLAUCOMA; OPTICAL COHERENCE TOMOGRAPHY DEVICE; PRIORITY JOURNAL; RANDOM FOREST; RECEIVER OPERATING CHARACTERISTIC; SPECTRAL DOMAIN OPTICAL COHERENCE TOMOGRAPHY; VALIDATION PROCESS; CLASSIFICATION; CLINICAL TRIAL; COMPARATIVE STUDY; DIAGNOSTIC IMAGING; FOLLOW UP; GLAUCOMA, OPEN-ANGLE; GONIOSCOPY; INTRAOCULAR PRESSURE; MULTICENTER STUDY; NERVE FIBER; OPTIC DISK; OPTICAL COHERENCE TOMOGRAPHY; PATHOLOGY; PATHOPHYSIOLOGY; PHYSIOLOGY; PROCEDURES; VALIDATION STUDY; VISUAL FIELD;

EID: 85002156915     PISSN: 00029394     EISSN: 18791891     Source Type: Journal    
DOI: 10.1016/j.ajo.2016.11.001     Document Type: Article
Times cited : (48)

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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.