Ovarian Cancer Classification Accuracy Analysis Using 15-Neuron Artificial Neural Networks Model

Abstract

Ovarian cancer is a severe disease for older woman. Based on the research, ovarian cancer is the fifth commonly disease and the seventh causes of death for woman worldwide. For ovarian cancer classification problem, many researchers have performed using Artificial Neural Network (ANN). Classification accuracy is a significant factor for taking decision by the Doctors. Higher classification accuracy can help to take the decision by doctors for giving proper treatment. Accurate and early diagnosis can save lives and reduce the percentage of mortality. This study focuses classification accuracy analysis of ovarian cancer. The purpose of this study is to analyze the classification accuracy using 15-neuron ANN model. The proposed model is benchmarked on ovarian cancer dataset. The achieving result from the proposed model has been compared with the other four classification algorithms. The proposed model has achieved 98.7% ovarian cancer classification accuracy which is more promising and higher than other classification algorithms.