Publication:
Neural Network Design for the Recurrence Prediction of Post-Operative Non-Metastatic Kidney Cancer Patients

dc.authorscopusid35606864300
dc.authorscopusid55364715200
dc.authorscopusid11240177700
dc.contributor.authorTander, B.
dc.contributor.authorÖzmen, A.
dc.contributor.authorÖzden, E.
dc.date.accessioned2020-06-21T13:51:06Z
dc.date.available2020-06-21T13:51:06Z
dc.date.issued2016
dc.departmentOndokuz Mayıs Üniversitesien_US
dc.department-temp[Tander] Baran, Kadir Has Vocational School, Kadir Has Üniversitesi, Istanbul, Turkey; [Özmen] Atilla, Faculty of Engineering and Natural Sciences, Kadir Has Üniversitesi, Istanbul, Turkey; [Özden] Ender, School of Medicine, Ondokuz Mayis Üniversitesi, Samsun, Turkeyen_US
dc.description.abstractIn this paper, various post-operative recurrence estimation models called nomograms for the kidney cancer patients without any metastates are introduced and novel systems based on a Multilayer Perceptron Neural Network are designed to simplify and integrate the mentioned techniques which is believed to ease the physician' s post-operative follow up procedures. The parameters effecting the recurrence are the TNM stage, tumor size and nuclear (Fuhrman) grade, the existance of necrosis and vascular invasion. Independent systems for two of the individual prediction methods, as well as a system that combines these are designed and performance analyses are carried out to verify the reliability. © 2015 Chamber of Electrical Engineers of Turkey.en_US
dc.identifier.doi10.1109/ELECO.2015.7394627
dc.identifier.endpage165en_US
dc.identifier.isbn9786050107371
dc.identifier.scopus2-s2.0-84963801089
dc.identifier.startpage162en_US
dc.identifier.urihttps://doi.org/10.1109/ELECO.2015.7394627
dc.identifier.wosWOS:000380410800032
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof-- 9th International Conference on Electrical and Electronics Engineering, ELECO 2015 -- 2015-11-26 through 2015-11-28 -- Bursa -- 119202en_US
dc.relation.journal2015 9Th International Conference on Electrical and Electronics Engineering (Eleco)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.titleNeural Network Design for the Recurrence Prediction of Post-Operative Non-Metastatic Kidney Cancer Patientsen_US
dc.typeConference Objecten_US
dspace.entity.typePublication

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