Multicategory classification of 11 neuromuscular diseases based on microarray data using support vector machine

2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014

Volumn , Issue , 2014, Pages 3460-3463

  Beom Choi, Soo ^a   Park, Jee Soo ^b   Chung, Jai Won ^a   Yoo, Tae Keun ^a   Kim, Deok Won ^b  

^a Yonsei University   (South Korea)

^b Yonsei University College of Medicine   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COST EFFECTIVENESS; DIAGNOSIS; DIRECTED GRAPHS; DISEASE CONTROL; FEATURE EXTRACTION; GENES; LEARNING ALGORITHMS; NEUROMUSCULAR REHABILITATION; NEUROPHYSIOLOGY; SUPPORT VECTOR MACHINES;

COST EFFECTIVE STRATEGIES; DIRECTED ACYCLIC GRAPH (DAG); DUCHENNE MUSCULAR DYSTROPHIES; FEATURE SELECTION METHODS; MACHINE LEARNING METHODS; MULTI-CATEGORY CLASSIFICATION; NATIONAL CENTER FOR BIOTECHNOLOGY INFORMATIONS; THREE FOLD CROSS VALIDATION;

CLASSIFICATION (OF INFORMATION);

CASE CONTROL STUDY; CLASSIFICATION; DATA BASE; DNA MICROARRAY; GENETICS; HUMAN; NEUROMUSCULAR DISEASE; SUPPORT VECTOR MACHINE; THEORETICAL MODEL;

CASE-CONTROL STUDIES; DATABASES AS TOPIC; HUMANS; MODELS, THEORETICAL; NEUROMUSCULAR DISEASES; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; SUPPORT VECTOR MACHINES;

EID: 84944903179     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/EMBC.2014.6944367     Document Type: Conference Paper

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