title: [Expert system for aiding diagnosis in hearing tests].
abstract: For expert systems intended to aid diagnosis, a structure with five levels is proposed. These levels are the original area, the parameter and a reduced parameter layer, the classification and the final-decision layer. On the basis of this structures, an expert system was developed specifically for neonatal hearing screening with transitory evoked otoacoustic emissions (TEOAE). In a second step, this system was investigated for its suitability to classify emissions, regardless of patient age. For the comparison measurements in 252 mainly adult patients, some with an acquired hearing impairment, were used. To adapt the pass/fail decision to the extended evaluation criteria, the false classifications from a first run with the new data were used for training. Thereafter, the expert system, working with a wider data basis, classified the new data with a sensitivity that was increased by 4.8% to 97.2%, and a 2.0% improvement in specificity to 95.5% when classifying new data, These results, together with those of 97.3% and 94.3% achieved with exclusively neonatal TEOAE classification, clearly show the advantage of the expert system structures chosen, and document evidence of the practical applicability of the method.
authors.affiliation: Hochschule Wismar, Fachbereich Elektrotechnik und Informatik. g.buller@et.hs-wismar.de
authors.forename: G
authors.initials: G
authors.lastname: Buller
authors.forename: S
authors.initials: S
authors.lastname: Hoth
authors.forename: S
authors.initials: S
authors.lastname: Suchandt
mesh_terms: D000328:Adult; D001185:Artificial Intelligence; D003936:Diagnosis, Computer-Assisted / Q000295:instrumentation*; D005103:Expert Systems; D006801:Humans; D007231:Infant, Newborn; D015997:Neonatal Screening / Q000295:instrumentation*; D017084:Otoacoustic Emissions, Spontaneous / Q000502:physiology*