Abstract
This paper discusses the characteristics of medical reasoning and shows the representation of these diagnostic models by the use of rough set theory. The key ideas are both a variable precision rough set model, which corresponds to an ordinal positive reasoning, and an upper approximation of a target concept, which corresponds to a focusing procedure. Acquired representation suggests that rough set model should be closely related with medical diagnosis.
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References
Buchnan, B. G. and Shortliffe, E. H. (eds.) (1984). Rule-Based Expert Systems, Addison-Wesley.
Langley, P. (1996). Elements of Machine Learning, Morgan Kaufmann, CA.
Mclachlan, G.J. (1992). Discriminant Analysis and Statistical Pattern Recognition. John Wiley and Sons, NY.
Michalski, R. S. (1983). A Theory and Methodology of Machine Learning. Michalski, R.S., Carbonell, J.G. and Mitchell, T.M., Machine Learning-An Artificial Intelligence Approach. Morgan Kaufmann, CA.
Pawlak, Z. (1991). Rough Sets. Kluwer Academic Publishers, Dordrecht.
Slowinski, K. et al. (1988). Rough sets approach to analysis of data from peritoneal lavage in acute pancreatitis. Medical Informatics, 13, 143–159.
Tsumoto, S. and Tanaka, H. (1995). PRIMEROSE: Probabilistic Rule Induction Method based on Rough Sets and Resampling Methods. Computational Intelligence, 11, 389–405.
Tsumoto, S. and Tanaka, H. (1996). Automated Discovery of Medical Expert System Rules from Clinical Databases based on Rough Sets. Proceedings of the Second International Conference on Knowledge Discovery and Data Mining 96, pp. 63–69, AAAI Press.
Tsumoto, S. and Tanaka, H. (1998). Automated Knowledge Acquisition from Medical Databases and Its Evaluation, MEDINFO-98, IMIA(in press).
Wakulicz-Deja, A., Paszek, P. (1997). Optimization on decision problems on medical knowledge bases. in: Proceedings of EUFIT-97.
Ziarko, W (1993). Variable Precision Rough Set Model. Journal of Computer and System Sciences, 46, 39–59.
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© 1998 Springer-Verlag Berlin Heidelberg
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Tsumoto, S. (1998). Modelling Medical Diagnostic Rules Based on Rough Sets. In: Polkowski, L., Skowron, A. (eds) Rough Sets and Current Trends in Computing. RSCTC 1998. Lecture Notes in Computer Science(), vol 1424. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-69115-4_65
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DOI: https://doi.org/10.1007/3-540-69115-4_65
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