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Intelligent dialogue based on statistical models of clinical decision‐making
Author(s) -
McSherry D. M. G.
Publication year - 1986
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4780050514
Subject(s) - computer science , bayesian probability , artificial intelligence , independence (probability theory) , machine learning , acute abdominal pain , conditional independence , bayesian network , management science , medicine , abdominal pain , statistics , mathematics , gastroenterology , economics
The independence Bayesian model has been used widely in computer programs designed to support clinical decision‐making. A reasoning strategy has been developed to enable these programs to conduct clinically pertinent dialogue and explain their reasoning. It has been implemented in a program for the diagnosis of acute abdominal pain based on the Bayesian model of de Dombal et al. Several features of the dialogue design have been adopted from artificial intelligence research, including shared initiative and critiquing. The program adopts a flexible goal‐driven strategy, attempting to confirm the clinician's diagnosis or rule out the likeliest alternative. Symptoms and signs are selected in order of their expected weights of evidence in favour of the hypothesized disease.