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Volumn 235, Issue , 2014, Pages 130-137

Automatic sleep classification using a data-driven topic model reveals latent sleep states

Author keywords

Automatic sleep classification; Electroencephalography (EEG); Electrooculography (EOG); Neurodegenerative diseases; Sleep state switching; Topic modeling

Indexed keywords

ARTICLE; AUTOMATIC SLEEP CLASSIFIER; BAYES THEOREM; CLASSIFICATION ALGORITHM; CLASSIFIER; CONTROLLED STUDY; ELECTROENCEPHALOGRAPHY; ELECTROOCULOGRAPHY; HUMAN; IDIOPATHIC DISEASE; LATENT DIRICHLET ALLOCATION MODEL; MAJOR CLINICAL STUDY; NONREM SLEEP; PARASOMNIA; PARKINSON DISEASE; PERIODIC LIMB MOVEMENT DISORDER; PRIORITY JOURNAL; REM SLEEP; SLEEP; SLEEP STAGE; AGED; AUTOMATED PATTERN RECOGNITION; BRAIN; EYE; FEMALE; MALE; MIDDLE AGED; PATHOPHYSIOLOGY; PHYSIOLOGY; POLYSOMNOGRAPHY; PROBABILITY; PROCEDURES; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING; VALIDATION STUDY; VISUAL SYSTEM FUNCTION;

EID: 84904872865     PISSN: 01650270     EISSN: 1872678X     Source Type: Journal    
DOI: 10.1016/j.jneumeth.2014.07.002     Document Type: Article
Times cited : (39)

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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.