An efficient diagnosis system for Parkinson's disease using kernel-based extreme learning machine with subtractive clustering features weighting approach

Computational and Mathematical Methods in Medicine

Volumn 2014, Issue , 2014, Pages

  Ma, Chao ^a   Ouyang, Jihong ^a   Chen, Hui Ling ^b   Zhao, Xue Hua ^a  

^a JILIN UNIVERSITY   (China)

^b WENZHOU UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTER AIDED DIAGNOSIS; KNOWLEDGE ACQUISITION; SUPPORT VECTOR MACHINES;

10-FOLD CROSS-VALIDATION; CLASSIFICATION ACCURACY; CLASSIFICATION RESULTS; DIAGNOSTIC ACCURACY; EXTREME LEARNING MACHINE; PARKINSON'S DISEASE; RECEIVER OPERATING CHARACTERISTIC CURVES; SUBTRACTIVE CLUSTERING;

LEARNING SYSTEMS;

ARTICLE; CLASSIFICATION ALGORITHM; DIAGNOSTIC ACCURACY; HUMAN; KERNEL BASED EXTREME LEARNING MACHINE; KERNEL METHOD; MACHINE LEARNING; PARKINSON DISEASE; REGRESSION ANALYSIS; SENSITIVITY AND SPECIFICITY; AGED; ALGORITHM; AREA UNDER THE CURVE; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; COMPUTER ASSISTED DIAGNOSIS; COMPUTER PROGRAM; FACTUAL DATABASE; MIDDLE AGED; PATHOPHYSIOLOGY; PROCEDURES; RECEIVER OPERATING CHARACTERISTIC; REPRODUCIBILITY; STATISTICAL MODEL; VERY ELDERLY;

AGED; AGED, 80 AND OVER; ALGORITHMS; AREA UNDER CURVE; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; DATABASES, FACTUAL; DIAGNOSIS, COMPUTER-ASSISTED; HUMANS; MIDDLE AGED; MODELS, STATISTICAL; PARKINSON DISEASE; REPRODUCIBILITY OF RESULTS; ROC CURVE; SENSITIVITY AND SPECIFICITY; SOFTWARE;

EID: 84914689062     PISSN: 1748670X     EISSN: 17486718     Source Type: Journal    
DOI: 10.1155/2014/985789     Document Type: Article

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