Deep learning for liver disease prediction

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dc.authoridAlaa Ali Hameed / 0000-0002-8514-9255en_US
dc.authorscopusidAlaa Ali Hameed / 56338374100en_US
dc.authorwosidAlaa Ali Hameed / ABI-8417-2020
dc.contributor.authorMutlu, Ebru Nur
dc.contributor.authorDevim, Ayse
dc.contributor.authorHameed, Alaa Ali
dc.contributor.authorJamil, Akhtar
dc.date.accessioned2022-06-13T13:49:45Z
dc.date.available2022-06-13T13:49:45Z
dc.date.issued2022en_US
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.description.abstractMining meaningful information from huge medical datasets is a key aspect of automated disease diagnosis. In recent years, liver disease has emerged as one of the commonly occurring diseases across the world. In this paper, a Convolutional Neural Network (CNN) based model is proposed for the identification of liver disease. Furthermore, the performance of CNN was also compared with traditional machine learning approaches, which include Naive Bayes (NB), Support Vector Machine (SVM), K-nearest Neighbors (KNN), and Logistic Regression (LR). For evaluation, two datasets were used: BUPA and ILPD. The experimental results showed that CNN was effective for the classification of liver disease, which produced an accuracy of 75.55%, and 72.00% on the BUPA and ILPD datasets, respectively. © 2022, Springer Nature Switzerland AG.en_US
dc.identifier.citationMutlu, E. N., Devim, A., Hameed, A. A., & Jamil, A. (2022). Deep learning for liver disease prediction doi:10.1007/978-3-031-04112-9_7 Retrieved from www.scopus.comen_US
dc.identifier.doi10.1007/978-3-031-04112-9_7en_US
dc.identifier.endpage107en_US
dc.identifier.issn1865-0929en_US
dc.identifier.scopus2-s2.0-85128878236en_US
dc.identifier.scopusqualityQ4en_US
dc.identifier.startpage95en_US
dc.identifier.urihttps://doi.org/10.1007/978-3-031-04112-9_7
dc.identifier.urihttps://hdl.handle.net/20.500.12713/2884
dc.identifier.volume1543en_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorHameed, Alaa Ali
dc.language.isoenen_US
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.relation.ispartofCommunications in Computer and Information Scienceen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectConvolutional Neural Networksen_US
dc.subjectDisease Classificationen_US
dc.subjectLiver Diseases Classificationen_US
dc.subjectMachine Learningen_US
dc.titleDeep learning for liver disease predictionen_US
dc.typeConference Objecten_US

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