Abstract
In this paper, we present the clinical evaluation of HEPAR, an intelligent system for hepatitis prognosis and liver transplantation decision support in an UCI medical database. The prognosis process, linguistic variables and their values were modeled based on expert’s knowledge the statistical analysis of the records of patients from the existed medical database and relevant literature. The system infers from rules the elements relating to prognosis and liver transplantation by combining the risk scores with weights which can vary dynamically through fuzzy calculations. First we introduce the medical problem, the design approach to the development of the fuzzy expert system and the computer environment. Then we present HEPAR architecture, the reasoning techniques in comparison with the probabilistic characteristics of the medical database. Finally we indicate a few details of the implementation. The expert system has been implemented in FuzzyCLIPS. The fuzzy rules are organized in groups to be able to simulate the diagnosis process. Experimental results showed that HEPAR did quite s well as the expert did.
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Koutsojannis, C., Koupparis, A., Hatzilygeroudis, I. (2009). HEPAR: An Intelligent System for Hepatitis Prognosis and Liver Transplantation Decision Support. In: Koutsojannis, C., Sirmakessis, S. (eds) Tools and Applications with Artificial Intelligence. Studies in Computational Intelligence, vol 166. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88069-1_13
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DOI: https://doi.org/10.1007/978-3-540-88069-1_13
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