期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2017
卷号：17
期号：2
出版社：International Journal of Computer Science and Network Security
摘要：The accessibility of large amounts of medicinal data in clinics and hospitals pointers to the focus on reliable information analysis software to exploit useful information. Many tools tried to diagnosis hepatitis disease but still there is a deficiency of analyzing the biological data of Hepatitis illness in the world, where millions of people are killed in the world by this disease. This research aims at investigating the neural network algorithm for hepatitis disease. The data mining processes applied on the UCI dataset. Our investigation model examined different types of neural network algorithms (Quick, Multiple, Dynamic and RBFN) with different factors such as data size, learning cycle, and processing time to achieve the diagnosis accuracy and estimated error. The Multiple neural networks proved the best performance compared with Quick, Dynamic, and RBF neural network algorithms.
