Abstract
The first article on fuzzy set theory appeared in 1965 [8]. Since then, the number of publications in this area has grown to over 15 000. Many of these contributions are in mathematical areas (topology, analysis, graph theory, logic). To an increasing degree, however, this theory has been applied to various areas and has resulted in methods, tools, and approaches which could be called “fuzzy technology”. In particular, since the end of the 1980s, when Japanese successes triggered the “fuzzy boom” in Europe and somewhat later in the USA, fuzzy set theory has been applied to decision-support systems, to diagnostic problems, to control problems, to pattern recognition, and to other problems, and medicine is one of the areas into which fuzzy sets entered first. One of the major reasons for this might be the fact that a majority of the problem structures found in medicine are not of the crisp black-or-white type but rather of the more complicated more-or-less type. This contribution will introduce the basic paradigms, principles, and methods of fuzzy set theory and then sketch some of the better-known applications to decision support in the medical area.
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© 1995 Springer-Verlag Berlin Heidelberg
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Zimmermann, HJ. (1995). Decision Support via Fuzzy Technology. In: Schwilden, H., Stoeckel, H. (eds) Control and Automation in Anaesthesia. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-79573-2_1
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DOI: https://doi.org/10.1007/978-3-642-79573-2_1
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