Automated neonatal seizure detection: A multistage classification system through feature selection based on relevance and redundancy analysis

Clinical Neurophysiology

Volumn 117, Issue 2, 2006, Pages 328-340

  Aarabi, A ^a,b   Wallois, F ^a,b   Grebe, R ^b  

^a AMIENS UNIVERSITY HOSPITAL   (France)

^b UNIVERSITÉ DE PICARDIE JULES VERNE   (France)

Author keywords

EEG seizure detection; Feature redundancy; Feature relevance; Feature selection; Neonates; Neural network

Indexed keywords

ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOANALYSIS; CLASSIFICATION; CORRELATION ANALYSIS; ELECTROENCEPHALOGRAM; FEMALE; HUMAN; INFANT; MALE; PRIORITY JOURNAL; REDUNDANCY ANALYSIS; SEIZURE;

ALGORITHMS; COMPUTER SIMULATION; DIAGNOSIS, COMPUTER-ASSISTED; ELECTROENCEPHALOGRAPHY; HUMANS; INFANT; MODELS, NEUROLOGICAL; NEURAL NETWORKS (COMPUTER); SEIZURES; SENSITIVITY AND SPECIFICITY;

EID: 32444446490     PISSN: 13882457     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.clinph.2005.10.006     Document Type: Article

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