title: Supporting multi-level multi-perspective dynamic decision making in medicine.
abstract: Most medical decision problems are exceedingly complex and contain a large number of variables. Abstraction facilitates the process of building a decision model by allowing a model builder to work at a level of detail that he is most comfortable with; it is also useful in time-critical situations or when there is insufficient data to support complete specification of probabilities of the uncertain events. In this paper, we identify and formalize abstraction and refinement operations commonly used in model construction. We illustrate the use of these mechanisms with an example on the follow-up management of colorectal cancer patients after surgery.
authors.affiliation: Medical Computing Laboratory, School of Computing, National University of Singapore. sumans@comp.nus.edu.sg
authors.forename: S
authors.initials: S
authors.lastname: Sundaresh
authors.forename: T Y
authors.initials: TY
authors.lastname: Leong
authors.forename: P
authors.initials: P
authors.lastname: Haddawy
mesh_terms: D015179:Colorectal Neoplasms / Q000601:surgery / Q000628:therapy*; D003661:Decision Support Techniques; D006801:Humans; D008722:Methods