A Knowledge­Based Model Construction approach to Medical Decision Making

Liem Ngo, M.S., Peter Haddawy, Ph.D. Department of Electrical Engineering and Computer Science University of Wisconsin­Milwaukee, Milwaukee, Wisconsin 53201


We present a framework for representing the prob­ abilistic effects of actions and contingent treatment plans. Our language has a well­defined declarative semantics and we have developed an implemented al­ gorithm (named BNG) that generates Bayesian net­ works (BN) to compute the posterior probabilities of queries. In this paper we address the problem of pro­ jecting a contingent treatment plan by automatically constructing a structure of interrelated BNs, which we call a BN­graph, and applying the available propaga­ tion procedures on it. To address the optimal plan generation, we base our approach on the observation that normally the target plan space has a well­defined structure. We provide a language to describe plan spaces which resembles a programming language with loops and conditionals. We briefly present the proce­ dures for finding the optimal plan(s) from such speci­ fied plan spaces.