FESHDD: fuzzy expert system for hepatitis B diseases diagnosis
Date
2009
Authors
Neshat, M.
Yaghobi, M.
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Conference paper
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2009 Fifth International Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control, ICSCCW, 2009, pp.1-4
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5th International Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control, ICSCCW 2009 (2 Sep 2009 - 4 Sep 2009 : Famagusta, Cyprus)
Abstract
Expert or knowledge-based systems are the most common type of AIM (artificial intelligence in medicine) system in routine clinical use. They contain medical knowledge, usually about a very specifically defined task, and are able to reason with data from individual patients to come up with reasoned conclusions. Although there are many variations, the knowledge within an expert system is typically represented in the form of a set of rules. In this paper a fuzzy expert system has been designed for diagnosing the hepatitis B intensity rate. The main problem in determining the disease intensity is not having information about the data variation rate and its resulting effect on the system. A Hepatitis B data bank has been collected in accordance with the recent medical findings about this disease and the endorsement of a liver specialist. This bank has 300 records and each record has 7 fields. This bank has been assembled from patients presenting at the liver biopsy department of Imam Reza hospital Mashad, Iran. Using specialist research and experience strong inference rules have been attained. Thus, the accuracy oft the system in diagnosing the hepatitis B intensity is 94.4± 0.2%. This system is a great improvement in comparison with currently existing system.
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Copyright 2009 IEEE