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Interval-Valued Methods in Medical Decision Support Systems

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Interval-Valued Methods in Classifications and Decisions

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 378))

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Abstract

In this chapter we present the application of methods based on interval modeling and aggregation in OvaExpert computer support system [OvaExpert project homepage: http://ovaexpert.pl/en/] designed for ovarian tumor diagnosis (however applicable also in other medical fields). It was shown that such methods made it possible to reduce the negative impact of lack of data and lead to meaningful and accurate decisions [2,3,4,5,6,7,8,9,10]. Here the behavior of some new interval-valued operators in OvaExpert is shown, namely there are considered possible and necessary aggregation functions and aggregation functions with respect to admissible linear orders. These aggregation operators were not previously considered in OvaExpert. The results prove that these new aggregation operators may be competitive with others, especially if it comes to the cost matrix results.

There is a lot of work out there to take people out of the loop in things like medical diagnosis. But if you are taking humans out of the loop, you are in danger of ending up with a very cold form of AI that really has no sense of human interest, human emotions, or human values.

Louis B. Rosenberg

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Authors and Affiliations

  1. Faculty of Mathematics and Natural Sciences, University of Rzeszów, Rzeszów, Poland

    Urszula Bentkowska

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  1. Urszula Bentkowska
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Correspondence to Urszula Bentkowska .

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Bentkowska, U. (2020). Interval-Valued Methods in Medical Decision Support Systems. In: Interval-Valued Methods in Classifications and Decisions. Studies in Fuzziness and Soft Computing, vol 378. Springer, Cham. https://doi.org/10.1007/978-3-030-12927-9_6

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