A new paradigm for explaining and linking knowledge in diagnostic problem solving.
Medical expert systems frequently use causal models to capture knowledge and diagnostic-problem-solving expertise. A significant obstacle confronting these systems is providing informative explanations without prohibitive computational expense. The explanations should allow the user to understand the decisions of the expert system and obtain additional details when needed. A new method, called HyperExplain, has been devised to flexibly link explanations with conclusions generated by a causal reasoning system. This approach creates a patient specific explanatory (PSE) model for the medical expert system that provides decision support from a variety of perspectives. A key feature of this method is the ability to alter the focus of explanations depending upon the problem-solving context and patient manifestations. The method has been implemented in a program that provides diagnostic assistance to physicians in the domain of neurophysiology.
Jamieson
P W
PW
University of Kansas Medical Center, Kansas City.
D001185:Artificial Intelligence; D003936:Diagnosis, Computer-Assisted; D005103:Expert Systems; D008962:Models, Theoretical; D012984:Software; D014481:United States