Feature selection for better identification of subtypes of guillain-barré syndrome

Computational and Mathematical Methods in Medicine

Volumn 2014, Issue , 2014, Pages

  Hernández Torruco, José ^a   Canul Reich, Juana ^a   Frausto Solís, Juan ^b   Méndez Castillo, Juan José ^c  

^a UNIVERSIDAD JUÁREZ AUTÓNOMA DE TABASCO   (Mexico)

^b Boulevard Cuauhnáhuac 566   (Mexico)

^c Hospital General de Especialidades dr Javier Buenfil Osorio   (Mexico)

Author keywords

[No Author keywords available]

Indexed keywords

FEATURE EXTRACTION; STATISTICAL TESTS;

COMPUTATIONAL TECHNIQUE; CORRELATION BASED FEATURE SELECTIONS (CFS); EVALUATION MEASURES; FEATURE SUBSET; FILTER METHOD; INFORMATION GAIN; NEUROLOGICAL DISORDERS; RELEVANT FEATURES;

CLUSTERING ALGORITHMS;

ALGORITHM; ARTICLE; CORRELATION BASED FEATURE SELECTION; EXPERIMENTAL DESIGN; EXPERIMENTATION; GUILLAIN BARRE SYNDROME; HUMAN; INFORMATION PROCESSING; MACHINE LEARNING; MAJOR CLINICAL STUDY; NERVE CONDUCTION; SEROLOGY; AUTOMATED PATTERN RECOGNITION; BIOLOGY; CLASSIFICATION; CLUSTER ANALYSIS; FACTUAL DATABASE; GUILLAIN-BARRE SYNDROME; PROCEDURES; REPRODUCIBILITY;

ALGORITHMS; CLUSTER ANALYSIS; COMPUTATIONAL BIOLOGY; DATABASES, FACTUAL; GUILLAIN-BARRE SYNDROME; HUMANS; NEURAL CONDUCTION; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS;

EID: 84930986694     PISSN: 1748670X     EISSN: 17486718     Source Type: Journal    
DOI: 10.1155/2014/432109     Document Type: Article

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