Predicting Tumor Category Using Artificial Neural Networks

ORIGINAL SOURCE
Originally published in TECHNICAL SCIENCE RESEARCH IN UZBEKISTAN; Vol. 2 No. 3 (2024): TECHNICAL SCIENCE RESEARCH IN UZBEKISTAN; 6-15.

Ibrahim, M. and Samy, S. (2024) Predicting Tumor Category Using Artificial Neural Networks. TECHNICAL SCIENCE RESEARCH IN UZBEKISTAN; Vol. 2 No. 3 (2024): TECHNICAL SCIENCE RESEARCH IN UZBEKISTAN; 6-15.

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Abstract

In this paper an Artificial Neural Network (ANN) model, for predicting the category of a tumor was developed and tested.
Taking patients’ tests, a number of information gained that influence the classification of the tumor. Such information as age, sex, histologic-type, degree-of-diffe, status of bone, bone-marrow, lung, pleura, peritoneum, liver, brain, skin, neck, supraclavicular, axillar, mediastinum, and abdominal. They were used as input variables for the ANN model. A model based on the Multilayer Perceptron Topology was established and trained using data set which its title is “primary tumor” and was obtained from the University Medical Centre, Institute of Oncology, Ljubljana, Yugoslavia
Test data evaluation shows that the ANN model is able to correctly predict the tumor category with  76.67 % accuracy.

Item Type: Article
Additional Information: Imported from Technical Science Research in Uzbekistan
SWORD Depositor: Admin User
Depositing User: Admin User
Date Deposited: 23 Sep 2026 22:41
Last Modified: 23 Sep 2026 22:41
URI: https://universalpublishings.uz/id/eprint/5827

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