Classification of Breast Cancer Patients Using Neural Network Technique

  • Putri Marhida Badarudin Universiti Tun Hussein Onn Malaysia, Malaysia
  • Rozaida Ghazali Universiti Tun Hussein Onn Malaysia, Malaysia
  • Abdullah Mohammed Abdullah Alahdal Hodeidah University, Yemen
  • N.A.M. Alduais Universiti Tun Hussein Onn Malaysia, Malaysia
  • Salama A Mostafa Universiti Tun Hussein Onn Malaysia, Malaysia
Keywords: Artificial neural network (ANN),, multi-layer, classification, breast cancer

Abstract

This work develops an Artificial Neural Network (ANN) model for performing Breast Cancer (BC) classification tasks. The design of the model considers studying different ANN architectures from the literature and chooses the one with the best performance. This ANN model aims to classify BC cases more systematically and more quickly. It provides facilities in the field of medicine to detect breast cancer among women. The ANN classification model is able to achieve an average accuracy of 98.88 % with an average run time of 0.182 seconds. Using this model, the classification of BC can be carried out much more faster than manual diagnosis and with good enough accuracy.

Published
15-04-2021
How to Cite
Badarudin, P. M., Ghazali, R., Alahdal, A. M. A., Alduais, N., & Mostafa, S. A. (2021). Classification of Breast Cancer Patients Using Neural Network Technique. Journal of Soft Computing and Data Mining, 2(1), 13-19. Retrieved from https://publisher.uthm.edu.my/ojs/index.php/jscdm/article/view/7474
Section
Articles