Detecting rare events using extreme value statistics applied to epileptic convulsions in children

Artificial Intelligence in Medicine

Volumn 60, Issue 2, 2014, Pages 89-96

  Luca, Stijn ^a   Karsmakers, Peter ^a   Cuppens, Kris ^a   Croonenborghs, Tom ^a   Van de Vel, Anouk ^b   Ceulemans, Berten ^b,c   Lagae, Lieven ^c,d   Van Huffel, Sabine ^a   Vanrumste, Bart ^a  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b ANTWERP UNIVERSITY HOSPITAL   (Belgium)

^c Epilepsy Centre for Children and Youth Pulderbos   (Belgium)

^d UNIVERSITY HOSPITALS LEUVEN   (Belgium)

Author keywords

Accelerometers; Epileptic; Extreme value theory; Hypermotor seizures; Unbalanced data; Unsupervised

Indexed keywords

EPILEPTIC; EXTREME VALUE THEORY; HYPERMOTOR SEIZURES; UNBALANCED DATA; UNSUPERVISED;

ELECTROPHYSIOLOGY;

ACCELEROMETERS;

ACCELEROMETER; ADOLESCENT; ARTICLE; CHILD; CLINICAL ARTICLE; ELECTROENCEPHALOGRAPHY; EXTREME VALUE THEORY; HOME MONITORING; HUMAN; KERNEL METHOD; NEUROLOGIST; PREDICTIVE VALUE; PRESCHOOL CHILD; PRIORITY JOURNAL; SCHOOL CHILD; SEIZURE; SENSITIVITY ANALYSIS; STATISTICAL MODEL; SUPPORT VECTOR MACHINE;

ACCELEROMETERS; EPILEPTIC; EXTREME VALUE THEORY; HYPERMOTOR SEIZURES; UNBALANCED DATA; UNSUPERVISED;

CHILD; EPILEPSY; HUMANS; MODELS, STATISTICAL; SOFTWARE;

EID: 84893732223     PISSN: 09333657     EISSN: 18732860     Source Type: Journal    
DOI: 10.1016/j.artmed.2013.11.007     Document Type: Article

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