Abstract
Facing the problem of mecical diagnosis assistance under uncertainty, whatever should be the adopted methodology, if based on fuzzy sets, the final step is to take a non-fuzzy decision, which means to assign some diagnosis to the patient. To tell it briefly, after some “fuzzyfication” of the problem comes the “defuzzification”. This defuzzification may be achieved by means of the separating power (of a fuzzy set). The separating power was first introduced by Dujet in 1980 [3], to solve the problem of finding the “best (crisp) partition” of a referential set, elements of which may satisfy a given property to some imprecise degree and was first applied to help for diagnosis in Inflammatory Syndroms by E. Sanchez and R. Bartolin in 1987.
Here is proposed a review of the methodology based on fuzzy sets which may be worked up, involving fuzzy measures and separating power. A rapid view about new mathematical results will follow, in order to show how to answer some specifical problems encountered in the “continuum” case.
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© 1991 Springer-Verlag Berlin Heidelberg
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Dujet, C., Si-Kaddour, H. (1991). Decision-Aid Under Uncertainty Based on Separating Power and Fuzzy Measures. In: Adlassnig, KP., Grabner, G., Bengtsson, S., Hansen, R. (eds) Medical Informatics Europe 1991. Lecture Notes in Medical Informatics, vol 45. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-93503-9_72
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DOI: https://doi.org/10.1007/978-3-642-93503-9_72
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