Graph-grammar productions for the modeling of medical dilemmas.
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.
Egar
J W
JW
Section on Medical Informatics, Stanford University School of Medicine, CA.
Musen
M A
MA
D001499:Bayes Theorem; D003198:Computer Simulation; D003658:Decision Making, Computer-Assisted; D012660:Semantics; D012984:Software; D014584:User-Computer Interface