Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6536
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dc.contributor.authorÜbeyli, Elif Derya-
dc.contributor.authorİlbay, Konuralp-
dc.contributor.authorİlbay, Gül-
dc.contributor.authorŞahin, Deniz-
dc.contributor.authorAkansel, Gür-
dc.date.accessioned2021-09-11T15:37:13Z-
dc.date.available2021-09-11T15:37:13Z-
dc.date.issued2010en_US
dc.identifier.issn0148-5598-
dc.identifier.issn1573-689X-
dc.identifier.urihttps://doi.org/10.1007/s10916-008-9239-4-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/6536-
dc.description.abstractThis paper illustrates the use of mixture of experts (ME) network structure to guide model selection for diagnosis of two subtypes of adult hydrocephalus (normal-pressure hydrocephalus-NPH and aqueductal stenosis-AS). The ME is a modular neural network architecture for supervised learning. Expectation-Maximization (EM) algorithm was used for training the ME so that the learning process is decoupled in a manner that fits well with the modular structure. To improve classification accuracy, the outputs of expert networks were combined by a gating network simultaneously trained in order to stochastically select the expert that is performing the best at solving the problem. The classifiers were trained on the defining features of NPH and AS (velocity and flux). Three types of records (normal, NPH and AS) were classified with the accuracy of 95.83% by the ME network structure. The ME network structure achieved accuracy rates which were higher than that of the stand-alone neural network models.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofJournal of Medical Systemsen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMixture of expertsen_US
dc.subjectExpectation-maximization algorithmen_US
dc.subjectNormal-pressure hydrocephalusen_US
dc.subjectAqueductal stenosisen_US
dc.subjectClassification accuracyen_US
dc.titleDifferentiation of Two Subtypes of Adult Hydrocephalus by Mixture of Expertsen_US
dc.typeArticleen_US
dc.departmentFaculties, Faculty of Engineering, Department of Electrical and Electronics Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümütr_TR
dc.identifier.volume34en_US
dc.identifier.issue3en_US
dc.identifier.startpage281en_US
dc.identifier.endpage290en_US
dc.authorid0000-0002-6752-0065-
dc.identifier.wosWOS:000277008200007en_US
dc.identifier.scopus2-s2.0-77954059589en_US
dc.institutionauthorÜbeyli, Elif Derya-
dc.identifier.pmid20503612en_US
dc.identifier.doi10.1007/s10916-008-9239-4-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ2-
item.openairetypeArticle-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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