Smart Doctor: Performance of Supervised ART-I Artificial Neural Network for Breast Cancer Diagnoses - AL-Rawi, Kamal R.; AL-Rawi, Saifaldeen K. (Iraqi Journal of Science, 2020)
Wisconsin Breast Cancer Dataset (WBCD) was employed to show the performance of the Adaptive Resonance Theory (ART), specifically the supervised ART-I Artificial Neural Network (ANN), to build a breast cancer diagnosis smart system. It was fed with different learning parameters and sets. The best result was achieved when the model was trained with 50% of the data and tested with the remaining 50%. Classification accuracy was compared to other artificial intelligence algorithms, which included fuzzy classifier, MLP-ANN, and SVM. We achieved the highest accuracy with such low learning/testing ratio.