Title: Breast Tissue Classification Using Artificial Neural Networks
Authors: Hiba waheed Elden Saleh
Samy S. Abu-Naser
Volume: 10
Issue: 7
Pages: 117-123
Publication Date: 2026/07/28
Abstract:
This research investigates the use of Artificial Neural Networks (ANNs) for breast tissue classification using the Breast Tissue dataset. The study applies Min-Max normalization as a preprocessing technique to improve data consistency and enhance model training performance. Several neural network architectures were evaluated using JustNN software to identify an effective model for classification. The results showed that the ANN model achieved high validation accuracy of approximately 95.45%, indicating its ability to learn complex patterns from medical data. Feature importance analysis revealed that Max IP, Area, and P were the most influential attributes in the classification process. The findings demonstrate that ANN can be an effective decision-support tool for breast tissue classification and may contribute to improving medical diagnosis accuracy.