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Volumn 41, Issue 12, 2018, Pages 2509-2516

An automated grading system for detection of vision-threatening referable diabetic retinopathy on the basis of color fundus photographs

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; AGED; AREA UNDER THE CURVE; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; AUSTRALIAN; CAUCASIAN; COHORT ANALYSIS; COLOR FUNDUS PHOTOGRAPH; CONTROLLED STUDY; CONVOLUTIONAL NEURAL NETWORK; DEEP LEARNING ALGORITHM; DIABETIC MACULAR EDEMA; DIABETIC RETINOPATHY; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; DIAGNOSTIC VALUE; DISEASE CLASSIFICATION; DISEASE SEVERITY; EXTERNAL VALIDATION; EYE PHOTOGRAPHY; FALSE NEGATIVE RESULT; FALSE POSITIVE RESULT; FEMALE; HUMAN; IMAGE ANALYSIS; IMAGE PROCESSING; IMAGE QUALITY; INDIGENOUS AUSTRALIAN; INTERNAL HOLD OUT VALIDATION; LEARNING ALGORITHM; MAJOR CLINICAL STUDY; MALAY (PEOPLE); MALE; OPHTHALMOLOGIST; PREDICTIVE VALUE; RETINA IMAGE; SENSITIVITY AND SPECIFICITY; STEREOSCOPIC VISION; VALIDATION PROCESS; VALIDATION STUDY; VISION; VISION THREATENING DIABETIC RETINOPATHY; ALGORITHM; AUSTRALIA; AUTOMATION; COMPUTER ASSISTED DIAGNOSIS; DEVICES; MASS SCREENING; MIDDLE AGED; PHOTOGRAPHY; PROCEDURES; VERY ELDERLY; VISUAL SYSTEM EXAMINATION;

EID: 85055705876     PISSN: 01495992     EISSN: 19355548     Source Type: Journal    
DOI: 10.2337/dc18-0147     Document Type: Article
Times cited : (208)

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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.