Author/Authors :
Lindgaard, Gitte IWK Health Centre, Canada , Pyper, Catherine Carleton University, Canada , Frize, Monique Carleton University, Canada , Walker, Robin IWK Health Centre, Canada , Boutilier, Craig University of Toronto, Canada , Hui, Bowen University of Toronto, Canada , Narasimhan, Sheila Carleton University, Canada , Folkens, Janette Carleton University, Canada , Winogron, Bill Potential, Almonte, Canada , Egan, Peter S4Potential, Canada , Jones, Colin S4Potential, Canada
Abstract :
Decision Support Systems are proliferating rapidly in many areas of human endeavour including clinical medicine and psychology. While these are typically based on rulebased systems, decision trees, or Artificial Neural Networks, this paper argues that Bayes’ Theorem can be applied fruitfully to support expert decisions both in dynamically changing situations requiring the system progressively to adapt, and when this is not the case. One example of each of these two types is given. One provides diagnostic support for human decision makers; the other, an e-health mental intervention system provides decision rules enabling it to respond and provide the most appropriate training modules to input from clients with changing needs. The contributions of psychological research underlying both systems is summarized
Keywords :
Bayes’ Theorem , Decision Support Systems (DSS) , diagnostic error , individuating information , base rates , e , health intervention
