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

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dc.contributor.authorŞentürk, Zehra Karapınar
dc.date.accessioned2023-07-26T11:50:15Z
dc.date.available2023-07-26T11:50:15Z
dc.date.issued2020
dc.departmentDÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_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.Keywords: diabetic retinopathy, artificial neural networks, Rapid Miner.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.trdizinid472027en_US
dc.identifier.urihttp://doi.org/10.16984/saufenbilder.630482
dc.identifier.urihttps://search.trdizin.gov.tr/yayin/detay/472027
dc.identifier.urihttps://hdl.handle.net/20.500.12684/12289
dc.identifier.volume24en_US
dc.indekslendigikaynakTR-Dizinen_US
dc.institutionauthorŞentürk, Zehra Karapınar
dc.language.isoenen_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.snmz$2023V1Guncelleme$en_US
dc.titleArtificial Neural Networks Based Decision Support System for the Detection of Diabetic Retinopathyen_US
dc.typeArticleen_US

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