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KP Adlassnig, G Kolarz (1986) "Representation and semiautomatic acquisition of medical knowledge in CADIAG-1 and CADIAG-2", Computers and Biomedical Research 19, 63--79

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Diagnostic Monitoring of Clinical Time Series - Steimann (1995)   (Correct)

....with multiple premises joined with logical and) the extension principle implies that the minimum is propagated to the output. It does, however, not cover uncertainty imposed by the inference itself: statements in the MYCIN [Shortliffe 76] style if premise then conclusion, CF = cf or CADIAG 2 [Adlassnig 86] style if antecedent then consequent with (O,C) are not provided for. 3.9 States and State Transitions From an observational standpoint, intelligent behaviour can be characterized by a system s varying response to identical input. Yet, intelligence is to be distinguished from indeterminacy ....

KP Adlassnig, G Kolarz (1986) "Representation and semiautomatic acquisition of medical knowledge in CADIAG-1 and CADIAG-2", Computers and Biomedical Research 19, 63--79


Fuzzy Medical Diagnosis - Steimann, Adlassnig   Self-citation (Adlassnig)   (Correct)

....with the disease (the consequent) Conversely, the strength of confirmation can be interpreted as the positive predictive value of the finding for the disease. This interpretation is particularly useful for the semi automatic detection of both relationships from existing clinical databases [Adlassnig 86] On the other hand, statements about the necessity and sufficiency found in textbooks usually contain terms such as mostly, seldom, very often, or strongly, which are mapped to fuzzy quantifiers in CADIAG 2 s knowledge representation. Examples of this are: mostly acute pancreatitis is ....

KP Adlassnig, G Kolarz "Representation and semiautomatic acquisition of medical knowledge in CADIAG-1 and CADIAG-2" Computers and Biomedical Research 19 (1986) 63--79.

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