Automated prediction of apnea and hypopnea, using a LAMSTAR artificial neural network

American Journal of Respiratory and Critical Care Medicine

Volumn 181, Issue 7, 2010, Pages 727-733

  Waxman, Jonathan A ^a,b   Graupe, Daniel ^a,b   Carley, David W ^a  

^a UNIVERSITY OF ILLINOIS AT CHICAGO   (United States)

^b UNIVERSITY OF ILLINOIS   (United States)

Author keywords

Breathing; Disordered; Obstructive; Sleep

Indexed keywords

ADULT; APNEA; ARTICLE; ARTIFICIAL NEURAL NETWORK; ELECTROMYOGRAPHY; FEMALE; HEART RATE VARIABILITY; HUMAN; HYPOPNEA INDEX; MAJOR CLINICAL STUDY; MALE; NONREM SLEEP; POLYSOMNOGRAPHY; PRIORITY JOURNAL; REM SLEEP; SENSITIVITY AND SPECIFICITY; SLEEP APNEA SYNDROME; ELECTRODIAGNOSIS; HOSPITALIZATION; METHODOLOGY; MIDDLE AGED; PATHOPHYSIOLOGY; PREDICTION AND FORECASTING; RISK ASSESSMENT; SLEEP STAGE;

ELECTRODIAGNOSIS; FEMALE; HUMANS; MALE; MIDDLE AGED; NEURAL NETWORKS (COMPUTER); POLYSOMNOGRAPHY; PREDICTIVE VALUE OF TESTS; RISK ASSESSMENT; SEVERITY OF ILLNESS INDEX; SLEEP APNEA SYNDROMES; SLEEP STAGES;

EID: 77951895223     PISSN: 1073449X     EISSN: 15354970     Source Type: Journal    
DOI: 10.1164/rccm.200907-1146OC     Document Type: Article

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