Summary
Theoretical fuzzy decision-making models mostly developed by Zadeh, Bellman, Jain and Yager can be adopted as useful tools to estimation of the total effectiveness-utility of a drug when appreciating its positive influence on a collection of symptoms characteristic of a considered diagnosis. The expected effectiveness of the medicine is evaluated by a physician as a verbal expression for each distinct symptom. By converting the words at first to fuzzy sets and then numbers we can regard the effectiveness structures as entries of a utility matrix that constitutes the common basic component of all methods. We involve the matrix in a number of computations due to different decision algorithms to obtain a sequence of tested medicines in conformity with their abilities to soothe the unfavorable impact of symptoms. An adjustment of the large spectrum of applied fuzzy decision-making models to the extraction of the best medicines provides us with some deviations in obtained results but we are thus capable to select this method whose effects closest converge to the physicians’ judgments and expectations.
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© 2008 Springer-Verlag Berlin Heidelberg
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Rakus-Andersson, E. (2008). Decision-making Techniques in Ranking of Medicine Effectiveness. In: Sordo, M., Vaidya, S., Jain, L.C. (eds) Advanced Computational Intelligence Paradigms in Healthcare - 3. Studies in Computational Intelligence, vol 107. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77662-8_3
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DOI: https://doi.org/10.1007/978-3-540-77662-8_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77661-1
Online ISBN: 978-3-540-77662-8
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