The Quantitative Management of Linguistic Terms in a Knowledge Engineering Tool: Application to Medical Reasoning

The number of tools to develop expert systems is considerably increasing. In these tools particular attention is placed on user-interfaces, whereas no adequate concern is devoted to the representation and management of imprecision and/or uncertainty. This trend can also be observed in tools for the development of expert systems of a certain complexity, where the solution of this problem is left to the user. This aspect is on the other hand particularly important if we try to develop an expert system in the medical field. In such a context, virtually all the data used to characterize facts and concepts contain some sort of variability, as confirmed, for instance, by the following sentence [7]: ... A problem we quickly uncovered in attempting to characterize arrhythmias was that there was inherent variability in virtually every interval... measured from the electrocardiogram. In order to represent this inherent variability we created a group of constants called epsilon (e). In many cases it was not possible to give the actual value of each epsilon. Research must be carried out in order to determine the value range associated with these epsilons. The epsilons provide the “fuzziness” which then can be used in an appropriate algorithm in mathematically characterizing the variability or uncertainty.

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