Abstract
In this chapter, a system named ISOR is presented, that supports research doctors to investigate and to explain cases that do not fit a theoretical hypothesis. The system is designed for situations where neither a well-developed theory nor reliable knowledge nor, at the beginning, a case base is available. Instead of theoretical knowledge and intelligent experience, just a theoretical hypothesis and a set of measurements are given. ISOR is a Case-Based Reasoning system. That means, when attempting to find an explanation for an exceptional case, solutions of already explained similar exceptional cases are considered. However, ISOR uses further knowledge sources, especially a dialog where the user (a research doctor) can make suggestions for an explanation. ISOR is domain independent and can be applied to various research problems. However, in this chapter, it is focused on the hypothesis that a specific exercise program improves the physical condition of dialysis patients. Since many data are missing for this research problem, a method to impute missing data was developed and is also presented here. This method combines general domain independent techniques with domain knowledge provided by a medical expert. For the latter technique Case-based Reasoning is applied again.
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Schmidt, R., Vorobieva, O. (2010). Explaining Medical Model Exceptions. In: Bichindaritz, I., Vaidya, S., Jain, A., Jain, L.C. (eds) Computational Intelligence in Healthcare 4. Studies in Computational Intelligence, vol 309. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14464-6_12
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DOI: https://doi.org/10.1007/978-3-642-14464-6_12
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