Ovarian Cancer Diagnosis Using Fuzzy Neural Networks Empowered By Evolutionary Clustering Technique

As computational power of modern computer increases exponentially, more efficient computerized solutions are possible for complex real world applications. However, the solutions are usually not interpretable to human beings such as the opaqueness of traditional neural networks. In this paper, we propose a fuzzy neural network that is empowered by genetic algorithm based rough set clustering (GARSC) technique. The system is capable to address real world problems not only with promising accuracy, but also with great interpretabilities. Ovarian cancer diagnosis is exploited to show its superior capabilities.