Statistics over features for internal carotid arterial disorders detection

Computers in Biology and Medicine

Volumn 38, Issue 3, 2008, Pages 361-371

  Übeyli, Elif Derya ^a  

^a TOBB UNIVERSITY OF ECONOMICS AND TECHNOLOGY   (Turkey)

Author keywords

Doppler signals; Eigenvector methods; Feature extraction selection; Lyapunov exponents; Mixture of experts; Modified mixture of experts

Indexed keywords

DIAGNOSIS; DOPPLER EFFECT; EIGENVALUES AND EIGENFUNCTIONS; FEATURE EXTRACTION; LYAPUNOV FUNCTIONS; MEDICAL PROBLEMS; ULTRASONIC IMAGING;

DOPPLER SIGNALS; EIGENVECTOR METHODS; LYAPUNOV EXPONENTS; MIXTURE OF EXPERTS; MODIFIED MIXTURE OF EXPERTS;

BLOOD VESSELS;

ARTICLE; CAROTID ARTERY DISEASE; CAROTID ARTERY OBSTRUCTION; CLINICAL ARTICLE; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DISEASE CLASSIFICATION; DOPPLER ECHOGRAPHY; HUMAN; INTERNAL CAROTID ARTERY; POWER SPECTRUM; PRIORITY JOURNAL; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS;

ADOLESCENT; ADULT; AGED; ALGORITHMS; ARTERIAL OCCLUSIVE DISEASES; CAROTID ARTERY DISEASES; CAROTID ARTERY, INTERNAL; CAROTID STENOSIS; EXPERT SYSTEMS; FEMALE; HUMANS; LIKELIHOOD FUNCTIONS; MALE; MIDDLE AGED; NEURAL NETWORKS (COMPUTER); REPRODUCIBILITY OF RESULTS; ROC CURVE; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED; ULTRASONOGRAPHY, DOPPLER;

EID: 39549089504     PISSN: 00104825     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compbiomed.2007.12.002     Document Type: Article

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