A novel classification and estimation approach for detecting keratoconus disease with intelligent systems

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dc.contributor.authorUcar, M.
dc.contributor.authorSen, B.
dc.contributor.authorCakmak, H.B.
dc.date.accessioned2024-09-29T16:20:58Z
dc.date.available2024-09-29T16:20:58Z
dc.date.issued2013
dc.departmentKarabük Üniversitesien_US
dc.description8th International Conference on Electrical and Electronics Engineering, ELECO 2013 -- 28 November 2013 through 30 November 2013 -- Bursa -- 102644en_US
dc.description.abstractKeratoconus is an eye disease characterized by progressive thinning of cornea which is the front based transparent layer of the eye. In other words, it is a progressive distortion of corneal layer and at least getting conical shape that should be like a dome camber. The vision reduces more and more while cornea gets shape of cone which should be like a sphere normally. The aim of this study is to define a new classification method for detecting keratoconus based on statistical analysis and to realize the prediction of these classified data with intelligent systems. 301 eyes of 159 patients and 394 eyes of 265 refractive surgery candidates as the control group have been used for this study. Factor analysis, one of the multivariate statistical techniques, has been mainly used to find more meaningful, easy to understand, and independent factors amongst the others. Later, a new classification method has been defined using clustering analysis techniques on these factors and finally estimated by using artificial neural networks and support vector machines. © 2013 The Chamber of Turkish Electrical Engineers-Bursa.en_US
dc.identifier.doi10.1109/eleco.2013.6713897
dc.identifier.endpage525en_US
dc.identifier.isbn978-605010504-9
dc.identifier.scopus2-s2.0-84894123321en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage521en_US
dc.identifier.urihttps://doi.org/10.1109/eleco.2013.6713897
dc.identifier.urihttps://hdl.handle.net/20.500.14619/9461
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIEEE Computer Societyen_US
dc.relation.ispartofELECO 2013 - 8th International Conference on Electrical and Electronics Engineeringen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectFactor analysisen_US
dc.subjectIntelligent systemsen_US
dc.subjectNeural networksen_US
dc.subjectSupport vector machinesen_US
dc.subjectClassification methodsen_US
dc.subjectClustering analysisen_US
dc.subjectControl groupsen_US
dc.subjectEstimation approachesen_US
dc.subjectEye diseaseen_US
dc.subjectMultivariate statistical techniquesen_US
dc.subjectRefractive surgeryen_US
dc.subjectTransparent layersen_US
dc.subjectMultivariant analysisen_US
dc.titleA novel classification and estimation approach for detecting keratoconus disease with intelligent systemsen_US
dc.typeConference Objecten_US

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