title: PROBES: a framework for probability elicitation from experts.
abstract: A decision analytic model represents uncertainties as probability distributions. These distributions are hard to assess especially for large and dynamic models. We propose an integrated framework that facilitates elicitation of the relevant probability distributions for dynamic decision models from the domain experts. The experts usually use some judgmental heuristics to aid probability assessments; the resulting distributions may be proned to cognitive biases. Our framework aims to minimize the effects of these biases and to improve the quality of decisions made. We have implemented a prototype system of the framework and evaluated its effectiveness via a case study in the follow-up management of colorectal cancer patients after curative surgery. Preliminary results demonstrate the practical promise of the framework.
authors.affiliation: Department of Computer Science, School of Computing, National University of Singapore. aikhiang@hotmail.com
authors.forename: A H
authors.initials: AH
authors.lastname: Lau
authors.forename: T Y
authors.initials: TY
authors.lastname: Leong
mesh_terms: D015179:Colorectal Neoplasms / Q000175:diagnosis / Q000628:therapy*; D003661:Decision Support Techniques; D005069:Evaluation Studies as Topic; D006801:Humans; D011336:Probability; D012008:Recurrence; D012984:Software