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Type-2 fuzzy diagnosis

Authors: Peter R. Innocent; Robert I. John;

Type-2 fuzzy diagnosis

Abstract

This paper describes a computationally fast and simple algorithm that produces an index of support for the diagnosis of diseases based on type-2 fuzzy sets. The procedure allows the specification of fuzzy symptoms by using fuzzy relations to determine a symptom's strength based on its observed intensity and the certainty of its duration. We formally describe the fuzzy approach and the algorithm, and show how it relates to a disease given a range of symptom strengths.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Average
Top 10%
Average
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