Title: Appendicitis diagnosis system using fuzzy logic- and neural network-based classifier

Authors: E. Sivasankar; R.S. Rajesh; S.R. Venkateshwaran

Addresses: Department of Computer Science and Engineering, National Institute of Technology, Tiruchrappalli-620015, Tamil Nadu, India. ' Department of Computer Science and Engineering, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, India. ' BHEL Hospital, Tiruchrappalli-620015, Tamil Nadu, India

Abstract: Clinical repositories containing large amounts of biological, clinical, and administrative data are increasingly becoming available as healthcare systems integrate patient information for research and utilisation objectives. Data mining techniques can be used to discover useful patterns by exploring and analysing clinical repositories. It is feasible to incorporate data mining techniques into the classification process to discover useful patterns for classification rules from training samples. This paper thus assess the role of the data mining techniques namely fuzzy logic-based classifier and a back propagation-based neural networks in the diagnosis of severity of appendicitis in patients presenting with right iliac fossa (RIF) pain. It is based on the statistics already collected about the presence of appendicitis from patients dataset of around 2,230 datasets collected from BHEL Hospital, Tiruchirappalli. The conclusion is that neuro fuzzy logic-based classifiers can be used an effective tool for accurately diagnosing the severity of appendicitis.

Keywords: data mining; fuzzy logic-based classifiers; back propagation neural networks; appendicitis severity; fuzzy logic; clinical repositories; medical diagnosis; right iliac fossa pain.

DOI: 10.1504/IJMEI.2011.044748

International Journal of Medical Engineering and Informatics, 2011 Vol.3 No.4, pp.337 - 350

Published online: 07 Mar 2015 *

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