2026-10-23T14:58:19Zhttps://gumushane-rdlopen.rawdatalibrary.net/oai/request

oai:gumushane-rdlopen.rawdatalibrary.net:gumushane/139552026-10-22T11:36:43Zopenairecom_gumushane_10000col_gumushane_10001com_gumushane_10007col_gumushane_10171

Tumor Classification via Subregion Combinations of Cortical L5PC6 Pyramidal NeuronsOzcan, ZubeyirBozkir, Ilknur KayikciogluKayikcioglu, TemelIEEEL5PC6pyramidal neuronsubregion stimulationtumor classificationIn this study, it was aimed to classify benign and malignant tumor samples by utilizing different subregions of a cortical L5PC6 pyramidal neuron. A spike-based learning method was applied to a real dataset, and a decision mechanism based on action potential generation was established by training a separate neuron for each class. During the training process, various types of synaptic connections and spike encoding schemes were evaluated and intensity coding yielded the highest performance for the pyramidal neuron. Regional analyses revealed that the basilar region particularly stood out in terms of classification success. The results demonstrate that the morphological and biophysical diversity of pyramidal neurons provides a significant advantage in classification tasks.Institute of Electrical and Electronics Engineers Inc.2025Conference Objecthttps://rdlopen.rawdatalibrary.net/r/gumushane/13955https://doi.org/10.1109/tiptekno68206.2025.11270125979-833155565-82687-7775trTIPTEKNO 2025 - Medical Technologies Congress, Proceedingsinfo:eu-repo/semantics/closedAccessinfo:eu-repo/semantics/conferenceObjecthttps://gumushane-rdlopen.rawdatalibrary.net/tr/items/gumushane/13955