It is considered a problem of harmonisation of diagnostic rules used in a distributed set of diagnostic centres, the rules being based on a k-most-similar-cases approach. Harmonisation is reached due to an exchange of diagnostic cases among the reference sets stored in the centres. The method is based on general concepts of similarity, semi-similarity and structural compatibility measures used to evaluation of adequacy of records in remote data files to the requirements connected with supporting decision making in a given, local diagnostic centre. The procedure of local reference set extension by diagnostic cases selection and acquisition is described. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Kulikowski, J. L. (2006). Harmonisation of soft logical inference rules in distributed decision systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4252 LNAI-II, pp. 235–242). Springer Verlag. https://doi.org/10.1007/11893004_30
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