The fuzzy receiver operating characteristic function and medical decisions with uncertainty

Receiver operating characteristic (ROC) methodology is an important tool in decision making where there are two outcomes. By introducing the notion of partial degree of membership, fuzzy ROC methodology extends classical ROC methodology as fuzzy set theory extends classical two-state set theory. Thi...

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Bibliographic Details
Published in[1990] Proceedings. First International Symposium on Uncertainty Modeling and Analysis pp. 694 - 699
Main Authors DeLeo, J.M., Campbell, G.
Format Conference Proceeding
LanguageEnglish
Published IEEE Comput. Soc. Press 1990
Subjects
Artificial intelligence
Artificial neural networks
Decision making
Fuzzy neural networks
Fuzzy set theory
Fuzzy systems
Hybrid intelligent systems
Learning
Medical expert systems
Set theory
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Summary:Receiver operating characteristic (ROC) methodology is an important tool in decision making where there are two outcomes. By introducing the notion of partial degree of membership, fuzzy ROC methodology extends classical ROC methodology as fuzzy set theory extends classical two-state set theory. This paper introduced fuzzy ROC methodology and demonstrates its importance in decision making. Computational methods are developed and important concepts are demonstrated with examples from clinical medicine. These concepts include objective derivation of fuzzy functions with linguistics modifiers, enhanced certainty in sequential case learning, fuzzy inferencing using multiple fuzzy variables and associations with artificial intelligence expert systems and neural networks.< >
ISBN:9780818621079
0818621079
DOI:10.1109/ISUMA.1990.151339