Decision-theoretic approach in knowledge-based system for consulting disease treatment

Abstract

Many researchers in such area as medicine are interested in developing methods for poviding computer-based decision support to the practicing physician. Although traditional researches have demonstrated the potential to provide useful computer-based consultation, they have paid little attention to the modeling of patient specific preferences and tradeoffs about the quantitative values which had been obtained from physicians. Furthermore, purely symbolic (non-quantitative) reasoning techniques have limited utility in the solution of many medical problems without the explicit consideration of the quantitative notions of uncertainty and tradeoffs. Because these issues are central in decision theory, it is often a more effective strategy to integrate ideas and techniques from symbolic reasoning and decision theory. Thus, this thesis attempts developing a computer-based clinical system for consulting disease treatment, called DACS(Decision-Analytic Consulting System), using decision tree, axioms of utility, and sensitivity analysis in decision-theoretic approach.