title: AI-based approach to automatic sleep classification.
abstract: The primary goal of this paper is to introduce the potential of artificial intelligence (AI) methods to researchers in sleep classification. AI provides learning procedures for the construction of a sleep classifier, prescribing how to combine the observed parameters and how to derive the corresponding decision thresholds. A case study reporting a successful application of an automatic induction of decision trees and of a learning vector quantizer to this domain is presented.
authors.affiliation: Ludwig-Boltzmann Institute of Medical Informatics and Neuroinformatics, Graz, Austria.
authors.forename: M
authors.initials: M
authors.lastname: Kubat
authors.forename: G
authors.initials: G
authors.lastname: Pfurtscheller
authors.forename: D
authors.initials: D
authors.lastname: Flotzinger
mesh_terms: D001185:Artificial Intelligence; D001331:Automation; D003663:Decision Trees; D006801:Humans; D012890:Sleep