Therapy Planning by Combining Ai and Decision Theoretic Techniques

Abstract

There is an increasing interest in therapy planning systems which combine artificial intelligence (AI) and decision theoretic techniques. Medical problems often require both categorical and probabilistic reasoning, but few systems try to combine them in general and homogeneous frameworks. This work presents the therapy advisor module of an expert system designed for managing anemic patients. This module allows simplest therapeutic problems to be solved by a frame-and-rule based expert system, and more complex problems, i.e. decisions that must be taken in presence of trade-offs, to be tackled by decision-theoretic techniques. Influence diagram formalism has been chosen to model the decision problem and methods for augmenting influence diagrams in order to describe temporal processes have been investigated. Decision analysis is an integrated part of the whole system, so that AI techniques provide help to the domain expert in building and debugging its own decision model.