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Title: Background knowledge in diagnosis
Authors: Dams, F.
Washbrook, John
Keravnou-Papailiou, Elpida
Keywords: Computer science;Artificial intelligence;Diagnosis;Expert systems (Computer science);Brain--Models
Issue Date: 1992
Publisher: Elsevier
Source: Artificial intelligence in medicine, 1992, Volume 4, Issue 4, Pages 263–279
Abstract: A diagnostic framework in which there is a clear separation between the expertise per se and relevant background knowledge is discussed. We argue for the need to have an explicit representation of background knowledge. Background knowledge is domain foundational knowledge or common-sense knowledge; it is brought into play in the diagnostic context activated by the foreground knowledge, the diagnostic expertise. In the diagnostic framework discussed, background knowledge is of two types: foundational knowledge related to diagnostic findings and common-sense knowledge about time. The explicit representation and integration of expert and background knowledge is essential for achieving competent behaviour, both from the perspectives of the conversational context and the diagnostic performance of the system. The framework presented is being applied successfully to the domain of skeletal dysplasias
ISSN: 0933-3657
Rights: © 1992 Published by Elsevier B.V.
Type: Article
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