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Soft Computing
Published in: Soft Computing 10/2011

01-10-2011 | Original Paper

A probabilistic interpretation of the medical expert system CADIAG-2

Author: David Picado Muiño

Published in: Soft Computing | Issue 10/2011

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Abstract

CADIAG-2 is a well-known expert system aimed at providing support for medical diagnose in the field of internal medicine. CADIAG-2 consists of a knowledge base in the form of a set of IF-THEN rules that relate distinct medical entities, in this paper interpreted as conditional probabilistic statements, and an inference engine constructed upon methods of fuzzy set theory. The aim underlying this paper is the understanding of the logical structure of the inference in CADIAG-2. To that purpose, we provide a (probabilistic) logical formalisation of the inference of the system and check its adequacy with probabilistic logic.
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Footnotes
1
Here (and throughout) ⊧ represents classical entailment.
 
2
We will be using the terms ‘satisfiable’ and ‘consistent’ indistinguishably.
 
3
Notice that such a rule is compatible with a probabilistic interpretation of v 0.
 
4
For the sake of brevity we will deal with sentences as if they were equivalence classes. If anything applies to a sentence of the form \(\neg\phi,\) with \(\phi\in SL,\) we also assume that it applies to any logical equivalent of \(\neg\phi\) without mentioning it.
 
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Metadata
Title
A probabilistic interpretation of the medical expert system CADIAG-2
Author
David Picado Muiño
Publication date
01-10-2011
Publisher
Springer-Verlag
Published in
Soft Computing / Issue 10/2011
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-011-0699-y

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