title: Intelligent dialogue based on statistical models of clinical decision-making.
abstract: 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.
mesh_terms: D000005:Abdomen; D001185:Artificial Intelligence; D001499:Bayes Theorem; D003658:Decision Making, Computer-Assisted; D003937:Diagnosis, Differential; D006801:Humans; D010146:Pain; D012984:Software