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Multi-Modal Reasoning Medical Diagnosis System Integrated With Probabilistic Reasoning

Tian, Jia, Chen, Xun and Dong, Shen-Ping (2005) Multi-Modal Reasoning Medical Diagnosis System Integrated With Probabilistic Reasoning. International Journal of Automation and Computing, 2 (2). pp. 134-143. ISSN 1476-8186

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Abstract

In this paper, a Multi Modal Reasoning (MMR) method integrated with probabilistic reasoning is proposed for the diagnosis support module of the open eHealth platform. MMR is based on both Rule Based Reasoning (RBR) and Case Based Reasoning (CBR). It is not only applied to the identification of diseases and syndromes based on medical guidelines,but also deals with exceptional cases and individual therapies in order to improve diagnostic accuracy. Moreover, a new rule expression frame is introduced to deal with uncertainty, which can represent and process vague, imprecise, and incomplete information. Furthermore, this system is capable of updating the attributes of rules and inducing rules with a small data sample.

Item Type: Article
Subjects: T Technology > T Technology (General)
Schools: School of Computing and Engineering
School of Computing and Engineering > Centre for Precision Technologies
School of Computing and Engineering > Centre for Precision Technologies > Advanced Machining Technology Group
School of Computing and Engineering > Diagnostic Engineering Research Centre
School of Computing and Engineering > Diagnostic Engineering Research Centre > Measurement System and Signal Processing Research Group
School of Computing and Engineering > Informatics Research Group
School of Computing and Engineering > Informatics Research Group > XML, Database and Information Retrieval Research Group
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Depositing User: Sharon Beastall
Date Deposited: 03 Mar 2011 13:02
Last Modified: 03 Mar 2011 13:02
URI: http://eprints.hud.ac.uk/id/eprint/9711

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