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rdf:type |
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lifeskim:mentions |
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pubmed:dateCreated |
1994-12-23
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pubmed:abstractText |
Iliad is a large medical diagnostic system that covers more than 2000 diagnoses and 9000 findings. Due to the size and the complexity of this system, a robust knowledge representation is essential to consistently and efficiently model the medical knowledge involved. In this paper, we describe the knowledge representation currently used in Iliad and a probabilistic representation based on the Bayesian network formalism which can be derived using the information that the Iliad knowledge base contains.
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pubmed:grant |
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pubmed:commentsCorrections |
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pubmed:language |
eng
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pubmed:journal |
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pubmed:citationSubset |
IM
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pubmed:status |
MEDLINE
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pubmed:issn |
0195-4210
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pubmed:author |
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pubmed:issnType |
Print
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
765-9
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pubmed:dateRevised |
2009-11-18
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pubmed:meshHeading |
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pubmed:year |
1994
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pubmed:articleTitle |
Automated transformation of probabilistic knowledge for a medical diagnostic system.
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pubmed:affiliation |
Department of Medical Informatics, University of Utah, Salt Lake City.
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pubmed:publicationType |
Journal Article,
Research Support, U.S. Gov't, P.H.S.
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