Tander, BaranÖzmen, AtillaÖzden, Ender2019-06-282019-06-28201619786050107371https://hdl.handle.net/20.500.12469/1296https://doi.org/10.1109/ELECO.2015.7394627In 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.eninfo:eu-repo/semantics/closedAccessConference Object162165WOS:00038041080003210.1109/ELECO.2015.73946272-s2.0-84963801089N/AN/A