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  • 1. Rakus-Andersson, Elisabeth
    Approximation of Clock-like Point Sets2007In: Studies in Fuzziness and Soft Computing, ISSN 1434-9922, E-ISSN 1860-0808, Vol. 202, p. 155-181+183-189Article in journal (Refereed)
    Abstract [en]

    This chapter has a theoretical character and can be studied by some medical staff researchers that seek methods of approximation of very irregular point sets. When the shape of an obtained polygon based on the point set is similar to a chain of bells, then it will be difficult to find a continuous standard curve that should approximate the polygon without making a large approximation error. The studies of some medical data give rise to the creation of polygons consisting of finite numbers of points tied together. Since the polygons are not formalized by some mathematical expressions, we suggest creating continuous functions that approximate them thoroughly in spite of their irregular shapes. To warrant a high accuracy of approximation, otherwise impossible to obtain when using standard curves, we test a continuous function composed of joined truncated π-functions or joined truncated s-functions. © 2007 Springer.

  • 2.
    Rakus-Andersson, Elisabeth
    Blekinge Institute of Technology, School of Engineering, Department of Mathematics and Science.
    Complementary Solutions in Diagnostic Models2007In: Studies in Fuzziness and Soft Computing, ISSN 1434-9922, E-ISSN 1860-0808, Vol. 212, p. 63-91Article in journal (Refereed)
    Abstract [en]

    We should admit that the case of patient P1 in Ex. 3.16 has not been very easy to solve especially when you consider the proper interpretation of PD3. By equipping us with equal values of the membership degrees it has not made it easy enough to make the proper choice of an unknown diagnosis. © 2007 Springer.

  • 3. Rakus-Andersson, Elisabeth
    Evaluation of Medicine Action Levels2007In: Studies in Fuzziness and Soft Computing, ISSN 1434-9922, E-ISSN 1860-0808, Vol. 212, p. 93-126Article in journal (Refereed)
    Abstract [en]

    In the previous chapters, we have discussed some ways of determining the most credible diagnosis in a patient who could be identified by his set of clinical symptoms. The same symptoms are usually found in several illnesses. Therefore, it is often difficult to recognize the value of each of their deterministic yet individual characteristics all at once. After improving the diagnostic model by adding complementary solutions we are at last aware of a diagnosis of the patient. The next step would be to prescribe him medication that will lead to a cure. It is seldom possible to give the patient only one remedy to remove completely all unfavourable symptoms. In order to broaden a list of medicines that complement each other, we usually want to evaluate levels of one medicine and its impact on all of the symptoms. Preferably, we want to estimate the lowest and the highest levels of effectiveness of the medicines tested, one by one, when considering their curative powers. © 2007 Springer.

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