title: Application of artificial intelligence in audiology.
abstract: In this paper, machine learning methods based on artificial intelligence theory are applied to the computer-aided decision making of some otoneurological diseases, for example Ménière's disease. Three methods explored are decision trees, genetic algorithms and neural networks. By using such a machine learning method, the decision-making program is trained with a representative training set of cases and tested with another set. The machine learning methods are useful also for our otoneurological expert system, One, which is based on a pattern recognition approach. The methods are able to differentiate most of the cases tested between the six diseases included, provided that a sufficiently large training set is available.
authors.affiliation: Department of Computer Science, University of Tampere, Finland. mj@mail.cs.uta.fi
authors.forename: M
authors.initials: M
authors.lastname: Juhola
authors.forename: K
authors.initials: K
authors.lastname: Viikki
authors.forename: J
authors.initials: J
authors.lastname: Laurikkala
authors.forename: Y
authors.initials: Y
authors.lastname: Auramo
authors.forename: E
authors.initials: E
authors.lastname: Kentala
authors.forename: I
authors.initials: I
authors.lastname: Pyykkö
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001298:Audiology; D004427:Ear Diseases / Q000175:diagnosis*; D005103:Expert Systems; D006801:Humans