Artificial Neural Networks Based Decision Support System for the Detection of Diabetic Retinopathy

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dc.contributor.authorKarapınar Şentürk, Zehra
dc.date.accessioned2025-10-11T20:42:42Z
dc.date.available2025-10-11T20:42:42Z
dc.date.issued2020
dc.departmentDüzce Üniversitesien_US
dc.description.abstractMachine learning methods have been frequently used for the diagnosis of several diseases recently because of its reliability and convenience. In this paper, a comprehensive overview of the literature related to diabetes and diabetic retinopathy has been done and diagnosis of diabetic retinopathy disease is investigated. Artificial Neural Networks (ANN) method has been applied to the problem using Rapid Miner, a data mining tool. Some other methods have also adapted to the problem, but ANN based detection approach gave the best results. 88.52% sensitivity has been obtained using the features of Messidor dataset. Besides showing the success of ANN in diabetic retinopathy detection, this study also proved that Rapid Miner can be used effectively for the analysis of diabetic retinopathy.en_US
dc.identifier.doi10.16984/saufenbilder.630482
dc.identifier.endpage431en_US
dc.identifier.issn2147-835X
dc.identifier.issue2en_US
dc.identifier.startpage424en_US
dc.identifier.urihttps://doi.org/10.16984/saufenbilder.630482
dc.identifier.urihttps://hdl.handle.net/20.500.12684/21231
dc.identifier.volume24en_US
dc.institutionauthorKarapınar Şentürk, Zehra
dc.language.isoenen_US
dc.publisherSakarya Universityen_US
dc.relation.ispartofSakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisien_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmzKA_DergiPark_20250911
dc.subjectArtificial Intelligenceen_US
dc.subjectYapay Zekaen_US
dc.titleArtificial Neural Networks Based Decision Support System for the Detection of Diabetic Retinopathyen_US
dc.typeArticle

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