Fuzzy set theory in medical diagnosis
IEEE Transactions on Systems, Man and Cybernetics
A theory of diagnosis from first principles
Artificial Intelligence
Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
GERTIS: a Dempster-Shafer approach to diagnosing hierarchical hypotheses
Communications of the ACM
The uncertain reasoner's companion: a mathematical perspective
The uncertain reasoner's companion: a mathematical perspective
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Analytic Calculi for Projective Logics
TABLEAUX '99 Proceedings of the International Conference on Automated Reasoning with Analytic Tableaux and Related Methods
Rule Based Expert Systems: The Mycin Experiments of the Stanford Heuristic Programming Project (The Addison-Wesley series in artificial intelligence)
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Which fuzzy logic is the best: Pragmatic approach (and its theoretical analysis)
Fuzzy Sets and Systems
On the (fuzzy) logical content of CADIAG-2
Fuzzy Sets and Systems
The consistency of the CADIAG-2 knowledge base: a probabilistic approach
LPAR'10 Proceedings of the 17th international conference on Logic for programming, artificial intelligence, and reasoning
Inferential models and relevant algorithms in a possibilistic framework
International Journal of Approximate Reasoning
Measuring and repairing inconsistency in probabilistic knowledge bases
International Journal of Approximate Reasoning
First-order satisfiability in Gödel logics: An NP-complete fragment
Theoretical Computer Science
A probabilistic interpretation of the medical expert system CADIAG-2
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Intelligent Systems, Design and Applications (ISDA 2009)
Artificial Intelligence in Medicine
Consistency checking of binary categorical relationships in a medical knowledge base
Artificial Intelligence in Medicine
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There is no established formal framework for expert systems based on weighted IF-THEN rules. We discuss three mathematical models that have been recently proposed by the authors for CADIAG-2-a well-known system of this kind. The three frameworks are based on fuzzy logics, probability theory and possibilistic logic, respectively. CADIAG-2 is used here as a case study to evaluate these frameworks. We point out their use, advantages and disadvantages. In addition, the described models provide insight into various aspects of CADIAG-2.