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Vol: 51(65) No: 3 / September 2006 Automatic Treatment of Knowledge Imperfection: Some Medical Applications T. Spircu Dept. of Medical Informatics, "Carol Davila" University of Medicine and Pharmacy, 8 Eroii Sanitari Blvd. Bucharest, Romania, e-mail: tspircu@univermed-cdgm.ro E. Roventa Computer Science Dept., Glendon College, York University, 2275 Bayview Ave., Toronto, Ontario, Canada, e-mail: Eroventa@yorku.ca Keywords: belief, fuzzy set, imprecise reasoning, possibility, t-norm. Abstract We investigate the connections between different kinds of knowledge imperfection and their compatible combination in medical reasoning. References [1] P. Degoulet, M. Fieschi, Introduction to Clinical Informatics, New York, Springer Verlag, 1999. [2] A. Dempster, “Upper and lower probabilities induced by a multivalued mapping”, Ann. of Math. Statistics, 38, pp. 325-339, 1967. [3] D. Dubois, H. Prade, “Fuzzy sets in approximate reasoning, I. Inference with possibility distributions”, Fuzzy Sets and Systems 40, pp.143-202, 1991. [4] G. J. Klir, B. Yuan, Fuzzy Sets and Fuzzy Logic. Theory and Applications. Upper Saddle River NJ, Prentice Hall, 1995. [5] J. Pearl, “Bayesian and belief-functions formalism for evidential reasoning: a conceptual analysis”, in: Readings in Uncertain Reasoning, J. Pearl and G. Shafer Eds., Palo Alto, Morgan Kaufmann Publ., 1989. [6] G. Shafer, A Mathematical Theory of Evidence, Princeton Univ. Press, 1976. [7] P. Smets, “Numerical representation of uncertainty”, in: Handbook of Defeasible Reasoning and Uncertainty Management Systems, Vol. 3. Belief Change, D.M. Gabbay and P. Smets Eds., Dordrecht, Kluwer Acad. Publ., pp. 265-309, 1998. [8] L. A. Zadeh, “A theory of approximative reasoning”, in: Machine Intelligence, J. E. Hayes, D. Mirchie and L. I. Kulich Eds., New York, Wiley, pp. 149-194, 1979. [9] L. A. Zadeh, “The role of fuzzy logic in the management of uncertainty in expert systems”, Fuzzy Sets and Systems 11, pp. 199-227, 1983. |