A Polynomial Neural Network Model for Prognostic Breast Cancer Prediction

 Abstract: The second leading cause of death among women is breast cancer. Once a patient is diagnosed with breast cancer, the prognosis gives the anticipated long-term behavior of the ailment. In this research breast cancer prognosis is done using Polynomial Neural Network (PNN) on Wisconsin Prognostic Breast Cancer (WPBC) dataset. The data pre-processing technique named Principal Component Analysis (PCA) is used as a features reduction transformation method to improve the accuracy of PNN.