An artificial neural network design for determination of hashimoto's thyroiditis sub-groups

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dc.contributor.authorAktan, Mehmet Emin
dc.contributor.authorAkdoğan, Erhan
dc.contributor.authorZengin, Namık
dc.contributor.authorGüney, Ömer Faruk
dc.contributor.authorParlar, Rabia Edibe
dc.date.accessioned10.07.201910:49:13
dc.date.accessioned2019-07-10T19:51:04Z
dc.date.available10.07.201910:49:13
dc.date.available2019-07-10T19:51:04Z
dc.date.issued2016
dc.departmentİstanbul Medipol Üniversitesi, Eczacılık Fakültesi, Eczacılık Meslek Bilimleri Bölümü, Klinik Eczacılık Ana Bilim Dalı
dc.descriptionCBU International Conference on Innovations in Science and Education (CBUIC) -- MAR 23-25, 2016 -- Prague, CZECH REPUBLIC
dc.descriptionWOS: 000392271000114
dc.description.abstractIn this study, an artificial neural network was developed for estimating Hashimoto's Thyroiditis subgroups. Medical analysis and measurements from 75 patients were used to determine the parameters most effective on disease sub-groups. The study used statistical analyses and an artificial neural network that was trained by the determined parameters. The neural network had four inputs: thyroid stimulating hormone, free thyroxine (fT4), right lobe size (RLS), and RLS2 - fT4(4), and two outputs for three groups: euthyroid, subclinical, and clinical. After training, the network was tested with data collected from 30 patients. Results show that, overall, the neural network estimated the sub-groups with 90% accuracy. Hence, the study showed that determination of Hashimoto's Thyroiditis sub-groups can be made via designed artificial neural network.
dc.description.sponsorshipCentral Bohemia University, Unicorn Collegeen_US
dc.identifier.citationAktan, M. E., Akdoğan, E., Zengin, N., Güney, Ö. F. ve Parlar, R. E. (2016). An artificial neural network design for determination of hashimoto's thyroiditis sub-groups. CBU International Conference on Innovations in Science and Education (CBUIC) içinde (756-762. ss.). Prague, Czech Republic, March 23-25, 2016. https://dx.doi.org/10.12955/cbup.v4.845
dc.identifier.doi10.12955/cbup.v4.845
dc.identifier.endpage762
dc.identifier.isbn978-80-88042-04-4
dc.identifier.issn1805-9961
dc.identifier.startpage756
dc.identifier.urihttps://dx.doi.org/10.12955/cbup.v4.845
dc.identifier.urihttps://hdl.handle.net/20.500.12511/2138
dc.identifier.volume4
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.language.isoen
dc.publisherCentral Bohemia University
dc.relation.ispartofCBU International Conference on Innovations in Science and Education (CBUIC)en_US
dc.relation.ispartofseriesCBU International Conference Proceedings
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectArtificial Neural Networks
dc.subjectHashimoto
dc.subjectThyroiditis
dc.subjectStatistical Analyze
dc.subjectDiagnosis
dc.titleAn artificial neural network design for determination of hashimoto's thyroiditis sub-groups
dc.typeConference Object

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