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|Title:||Making deepness explicit||Authors:||Washbrook, John
|Keywords:||Computer science;Artificial intelligence;Medicine;Expert systems (Computer science)||Issue Date:||1990||Publisher:||Elsevier||Source:||Artificial intelligence in medicine, 1990, Volume 2, Issue 3, Pages 129–134||Abstract:||The concept of deepness is a useful, if poorly defined, concept. In spite of the development over a number of years of several medical expert systems with high levels of performance, these systems have failed in that they have not been accepted by the medical community. The introduction of so-called deep systems, where deepness is often taken to be synonymous with embodying causality, was an approach to resolving this problem. Two systems, CASNET and NEOMYCIN, are compared and it is argued that although CASNET is deeper in that its reasoning is causal, NEOMYCIN is in fact more acceptable in that its explanations and dialogue are closer to those of an expert. The intuitive meaning of deepness is discussed, and a working definition is developed which is not based exclusively upon causality, but which includes the explicit representation of strategic and factual knowledge||URI:||http://ktisis.cut.ac.cy/handle/10488/7055||ISSN:||09333657||DOI:||http://dx.doi.org/10.1016/0933-3657(90)90043-Q||Rights:||© 1990 Published by Elsevier B.V.||Type:||Article|
|Appears in Collections:||Άρθρα/Articles|
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