Variable precision rough set model
Journal of Computer and System Sciences
Elements of machine learning
Rough Sets and Decision Algorithms
RSCTC '00 Revised Papers from the Second International Conference on Rough Sets and Current Trends in Computing
Induction of Classification Rules by Granular Computing
TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
Discovery of Positive and Negative Knowledge in Medical Databases Using Rough Sets
Progress in Discovery Science, Final Report of the Japanese Discovery Science Project
Medical Reasoning and Rough Sets
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
On Certain Rough Inclusion Functions
Transactions on Rough Sets IX
Transactions on rough sets XII
Pawlak rough set model, medical reasoning and rule mining
RSCTC'06 Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
Rough validity, confidence, and coverage of rules in approximation spaces
Transactions on Rough Sets III
Journal of Biomedical Informatics
Fundamenta Informaticae - To Andrzej Skowron on His 70th Birthday
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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.