Literature DB >> 1482895

Graph-grammar productions for the modeling of medical dilemmas.

J W Egar1, M A Musen.   

Abstract

We introduce graph-grammar production rules, which can guide physicians to construct models for normative decision making. A physician describes a medical decision problem using standard terminology, and the graph-grammar system matches a graph-manipulation rule to each of the standard terms. With minimal help from the physician, these graph-manipulation rules can construct an appropriate Bayesian probabilistic network. The physician can then assess the necessary probabilities and utilities to arrive at a rational decision. The grammar relies on prototypical forms that we have observed in models of medical dilemmas. We have found graph grammars to be a concise and expressive formalism for describing prototypical forms, and we believe such grammars can greatly facilitate the modeling of medical dilemmas and medical plans.

Mesh:

Year:  1992        PMID: 1482895      PMCID: PMC2248114     

Source DB:  PubMed          Journal:  Proc Annu Symp Comput Appl Med Care        ISSN: 0195-4210


  3 in total

1.  Probabilistic diagnosis using a reformulation of the INTERNIST-1/QMR knowledge base. I. The probabilistic model and inference algorithms.

Authors:  M A Shwe; B Middleton; D E Heckerman; M Henrion; E J Horvitz; H P Lehmann; G F Cooper
Journal:  Methods Inf Med       Date:  1991-10       Impact factor: 2.176

2.  Probabilistic diagnosis using a reformulation of the INTERNIST-1/QMR knowledge base. II. Evaluation of diagnostic performance.

Authors:  B Middleton; M A Shwe; D E Heckerman; M Henrion; E J Horvitz; H P Lehmann; G F Cooper
Journal:  Methods Inf Med       Date:  1991-10       Impact factor: 2.176

3.  Automated critiquing of medical decision trees.

Authors:  M P Wellman; M H Eckman; C Fleming; S L Marshall; F A Sonnenberg; S G Pauker
Journal:  Med Decis Making       Date:  1989 Oct-Dec       Impact factor: 2.583

  3 in total

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