Feature selection and classification methodology for the detection of knee-joint disorders

Computer Methods and Programs in Biomedicine

Volumn 127, Issue , 2016, Pages 94-104

  Nalband, Saif ^a   Sundar, Aditya ^a   Prince, A Amalin ^a   Agarwal, Anita ^a  

^a BIRLA INSTITUTE OF TECHNOLOGY AND SCIENCE   (India)

Author keywords

Apriori algorithm; Biomedical signal processing; Feature selection; Genetic algorithm; Vibroarthographic signal; Wavelets

Indexed keywords

BIOINFORMATICS; BIOMEDICAL SIGNAL PROCESSING; CLASSIFICATION (OF INFORMATION); DECISION TREES; DIAGNOSTIC PRODUCTS; ENTROPY; GENETIC ALGORITHMS; JOINTS (ANATOMY); LEARNING ALGORITHMS; NONINVASIVE MEDICAL PROCEDURES; SIGNAL PROCESSING; SUPPORT VECTOR MACHINES; WAVELET DECOMPOSITION;

APRIORI ALGORITHMS; FEATURE SELECTION AND CLASSIFICATION; LEAST SQUARE SUPPORT VECTOR MACHINE (LS-SVM); NON-INVASIVE DIAGNOSTICS; RECURRENCE QUANTIFICATION ANALYSIS; SIGNALS OF DIFFERENT FREQUENCIES; VIBROARTHOGRAPHIC SIGNALS; WAVELETS;

FEATURE EXTRACTION;

ACCURACY; ALGORITHM; APPROXIMATE ENTROPY; APRIORI ALGORITHM; ARTICLE; CLASSIFICATION; ENTROPY; FEATURE SELECTION; GENETIC ALGORITHM; KNEE DISEASE; LEAST SQUARE ANALYSIS; METHODOLOGY; RANDOM FOREST; RECURRENCE QUANTIFICATION ANALYSIS; SAMPLE ENTROPY; SIGNAL PROCESSING; SUPPORT VECTOR MACHINE; VIBROARTHOGRAPHY SIGNAL; WAVELET ANALYSIS; ARTHROPATHY; HUMAN; KNEE; NONLINEAR SYSTEM; PATHOLOGY; VIBRATION;

ALGORITHMS; HUMANS; JOINT DISEASES; KNEE JOINT; NONLINEAR DYNAMICS; VIBRATION;

EID: 84985996957     PISSN: 01692607     EISSN: 18727565     Source Type: Journal    
DOI: 10.1016/j.cmpb.2016.01.020     Document Type: Article

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