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Comparative study on computerised diagnostic performance of hepatitis disease using ANNs

dc.contributor.authorVural, Revna Acar
dc.contributor.authorOzyilmaz, Lale
dc.contributor.authorYildirim, Tulay
dc.contributor.institutionauthorYILDIRIM, Tülay
dc.date.accessioned2026-06-27T13:01:04Z
dc.date.issued2006
dc.description.abstractArtificial Neural Networks (ANNs) have been studied intensively in the field of computer science in recent years and have been shown to be a powerful tool for a variety of data-classification and pattern-recognition tasks. In this work, computerised diagnostic performance of hepatitis disease was investigated by various ANNs. Multilayer Perceptron, Radial Basis Function Neural Network, Conic Section Function Neural Network, Probabilistic Neural Network, and General Regression Neural Network structures have been used for this purpose. To determine diagnostic performance of networks for hepatitis disease, cross validation method and ROC analysis were applied.en
dc.identifier.eissn1611-3349
dc.identifier.endpage1182
dc.identifier.isbn3-540-37274-1
dc.identifier.issn0302-9743
dc.identifier.startpage1177
dc.identifier.urihttps://hdl.handle.net/20.500.14981/49032
dc.identifier.volume4114
dc.identifier.wos000240083300145
dc.language.isoeng
dc.publisherSPRINGER-VERLAG BERLIN
dc.relation.conferenceInternational Conference on Intelligent Computing (ICIC)
dc.relation.ispartofCOMPUTATIONAL INTELLIGENCE, PT 2, PROCEEDINGS
dc.subjectNETWORKS
dc.subjectComputer Science
dc.titleComparative study on computerised diagnostic performance of hepatitis disease using ANNs
dc.typeArticle; Proceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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