title: Seizure prediction: the impact of long prediction horizons.
abstract: Several procedures have been proposed to be capable of predicting the occurrence of epileptic seizures. Up to now, all proposed algorithms are far from being sufficient for a clinical application. This is, however, often not obvious when results of seizure prediction performance are reported. Here, we discuss impacts of long prediction horizons with respect to clinical needs and the strain on patients by analyzing long-term continuous intracranial electroencephalography data.
authors.affiliation: FDM, Freiburg Center for Data Analysis and Modeling, University of Freiburg, Eckerstr. 1, 79104 Freiburg, Germany. schelter@fdm.uni-freiburg.de
authors.forename: Björn
authors.initials: B
authors.lastname: Schelter
authors.forename: Matthias
authors.initials: M
authors.lastname: Winterhalder
authors.forename: Hinnerk
authors.initials: H
authors.lastname: Feldwisch genannt Drentrup
authors.forename: Johannes
authors.initials: J
authors.lastname: Wohlmuth
authors.forename: Jakob
authors.initials: J
authors.lastname: Nawrath
authors.forename: Armin
authors.initials: A
authors.lastname: Brandt
authors.forename: Andreas
authors.initials: A
authors.lastname: Schulze-Bonhage
authors.forename: Jens
authors.initials: J
authors.lastname: Timmer
mesh_terms: D000293:Adolescent; D000328:Adult; D004569:Electroencephalography; D004827:Epilepsy / Q000503:physiopathology*; D005189:False Positive Reactions; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008959:Models, Neurological; D011237:Predictive Value of Tests; D012640:Seizures / Q000503:physiopathology*; D012680:Sensitivity and Specificity