Document Detail


A diagnostic advice system based on pathophysiological models of diseases.
MedLine Citation:
PMID:  10724972     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Medical decision-support systems in which uncertainty plays an essential role are increasingly based on the formalism of probabilistic networks. Although this formalism is very powerful, the construction of actual networks is not straightforward, and requires the availability of clearly structured medical domain models as a starting point. In this paper it is argued that medical pathophysiological knowledge constitutes a good start for the development of such models, even though pathophysiological knowledge is semantically different from probabilistic knowledge. Two models concerning anaemia, which are part of a broad system covering the domain of anaemia, are discussed to illustrate the general approach.
Authors:
W J ter Burg; P Lucas; E ter Braak
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Studies in health technology and informatics     Volume:  68     ISSN:  0926-9630     ISO Abbreviation:  Stud Health Technol Inform     Publication Date:  1999  
Date Detail:
Created Date:  2000-02-24     Completed Date:  2000-02-24     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  9214582     Medline TA:  Stud Health Technol Inform     Country:  NETHERLANDS    
Other Details:
Languages:  eng     Pagination:  654-9     Citation Subset:  T    
Affiliation:
Department of Medical Informatics, Academic Medical Centre, University of Amsterdam, The Netherlands. W.J.terBurg@amc.uva.nl
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MeSH Terms
Descriptor/Qualifier:
Anemia, Pernicious / diagnosis,  etiology,  physiopathology
Bayes Theorem
Computer Simulation*
Decision Support Techniques*
Diagnosis, Computer-Assisted*
Diagnosis, Differential
Disease / etiology*
Humans
Models, Statistical

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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