Reference: Cooper, G. F. A Diagnostic Method That Uses Casual Knowledge and Linear Programming in the Application of Bayes' Formula. 1986.
Abstract: Bayes' formula has been applied extensively in computer-based medical diagnostic systems. One assumption that is often made in the application of the formula is that the findings in a case are conditionally independent. This assumption is often invalid and leads to inaccurate posterior probability assignments to the diagnostic hypotheses. This paper discusses a method for using casual knowledge to structure findings according to their probabilistic dependencies. An inference procedure is discussed which propagates probabilities within a network of casually related findings in order to calculate posterior probabilities of diagnostic hypotheses. A linear programming technique is described that bounds the values of the propagated probabilities subject to known probabilistic constraints.
Notes: Journal Memo.