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Advances in Artificial Neural Systems
Volume 2013 (2013), Article ID 539570, 7 pages
http://dx.doi.org/10.1155/2013/539570
Research Article

Intelligent Systems Developed for the Early Detection of Chronic Kidney Disease

1Department of Information Management, Fu Jen Catholic University, Xinzhuang District, New Taipei City 24205, Taiwan
2Office of Computer Processing, En Chu Kong Hospital, Sanxia District, New Taipei City 23702, Taiwan
3Office of Information Processing, Cardinal Tien Hospital, Xindian District, New Taipei City 231, Taiwan

Received 10 August 2012; Revised 5 November 2012; Accepted 5 November 2012

Academic Editor: Ping Feng Pai

Copyright © 2013 Ruey Kei Chiu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper aims to construct intelligence models by applying the technologies of artificial neural networks including back-propagation network (BPN), generalized feedforward neural networks (GRNN), and modular neural network (MNN) that are developed, respectively, for the early detection of chronic kidney disease (CKD). The comparison of accuracy, sensitivity, and specificity among three models is subsequently performed. The model of best performance is chosen. By leveraging the aid of this system, CKD physicians can have an alternative way to detect chronic kidney diseases in early stage of a patient. Meanwhile, it may also be used by the public for self-detecting the risk of contracting CKD.