Title: Expert systems and uncertainty in medical diagnosis: a proposal for fuzzy-ANP hybridisation

Authors: Faith-Michael E. Uzoka, Ken Barker

Addresses: Department of Computer Science and Information Systems, Mount Royal University, Calgary, T3E 6K6, Canada. ' Department of Computer Science, University of Calgary, Alberta, T2N 4N1, Canada

Abstract: Major research efforts in decision support systems for medical diagnosis have focused on the hypothesis testing and management of uncertain and imprecise decision variables aimed at obtaining optimal inferences. In this study, a survey of such systems and methods is carried out. The study identifies medical diagnosis as involving imprecise information in a multi-criteria decision situation. We propose a hybrid fuzzy based analytic network process (ANP) system for managing the hierarchical structuring and imprecision associated with medical diagnosis. The justification being that fuzzy-ANP system is capable of accommodating inherent uncertainty and vagueness in multi-attribute/multi-criteria decision-making with hierarchical structuring and feedback dependence.

Keywords: medical diagnosis; expert systems; uncertainty; hybrid systems; analytical hierarchy process; AHP; analytical network process; fuzzy ANP; fuzzy logic; intelligent diagnosis; decision support systems; DSS; imprecise information; multicriteria decision making; MCDM.

DOI: 10.1504/IJMEI.2010.036305

International Journal of Medical Engineering and Informatics, 2010 Vol.2 No.4, pp.329 - 342

Published online: 01 Nov 2010 *

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