Performance assessment for EEG-based neonatal seizure detectors

Clinical Neurophysiology

Volumn 122, Issue 3, 2011, Pages 474-482

  Temko, A ^a   Thomas, E ^a   Marnane, W ^a   Lightbody, G ^a   Boylan, G B ^a  

^a UNIVERSITY COLLEGE CORK   (Ireland)

Author keywords

Automated seizure detection; Machine learning; Metrics; Neonatal EEG; Performance assessment; Support Vector Machines

Indexed keywords

ALGORITHM; ARTICLE; CLINICAL ARTICLE; CLINICAL ASSESSMENT; CLINICAL PROTOCOL; DIAGNOSTIC TEST ACCURACY STUDY; ELECTROENCEPHALOGRAPHY; FALSE POSITIVE RESULT; HUMAN; MACHINE LEARNING; PRIORITY JOURNAL; SEIZURE; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE; TASK PERFORMANCE;

ALGORITHMS; ANISOTROPY; ARTIFICIAL INTELLIGENCE; DATA INTERPRETATION, STATISTICAL; DATABASES, FACTUAL; ELECTROENCEPHALOGRAPHY; HUMANS; INFANT; INFANT, NEWBORN; REPRODUCIBILITY OF RESULTS; ROC CURVE; SEIZURES;

EID: 78751633678     PISSN: 13882457     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.clinph.2010.06.035     Document Type: Article

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