dc.contributor.author | Aktan, Mehmet Emin | |
dc.contributor.author | Akdoğan, Erhan | |
dc.contributor.author | Zengin, Namık | |
dc.contributor.author | Güney, Ömer Faruk | |
dc.contributor.author | Parlar, Rabia Edibe | |
dc.date.accessioned | 10.07.201910:49:13 | |
dc.date.accessioned | 2019-07-10T19:51:04Z | |
dc.date.available | 10.07.201910:49:13 | |
dc.date.available | 2019-07-10T19:51:04Z | |
dc.date.issued | 2016 | en_US |
dc.identifier.citation | Aktan, 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 | en_US |
dc.identifier.isbn | 978-80-88042-04-4 | |
dc.identifier.issn | 1805-9961 | |
dc.identifier.uri | https://dx.doi.org/10.12955/cbup.v4.845 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12511/2138 | |
dc.description | CBU International Conference on Innovations in Science and Education (CBUIC) -- MAR 23-25, 2016 -- Prague, CZECH REPUBLIC | en_US |
dc.description | WOS: 000392271000114 | en_US |
dc.description.abstract | In 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. | en_US |
dc.description.sponsorship | Central Bohemia University, Unicorn College | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Central Bohemia University | en_US |
dc.relation.ispartofseries | CBU International Conference Proceedings | |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Artificial Neural Networks | en_US |
dc.subject | Hashimoto | en_US |
dc.subject | Thyroiditis | en_US |
dc.subject | Statistical Analyze | en_US |
dc.subject | Diagnosis | en_US |
dc.title | An artificial neural network design for determination of hashimoto's thyroiditis sub-groups | en_US |
dc.type | conferenceObject | en_US |
dc.relation.ispartof | CBU International Conference on Innovations in Science and Education (CBUIC) | en_US |
dc.department | İstanbul Medipol Üniversitesi, Eczacılık Fakültesi, Eczacılık Meslek Bilimleri Bölümü, Klinik Eczacılık Ana Bilim Dalı | en_US |
dc.identifier.volume | 4 | en_US |
dc.identifier.startpage | 756 | en_US |
dc.identifier.endpage | 762 | en_US |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.identifier.doi | 10.12955/cbup.v4.845 | en_US |