Fuzzy temporal categorical information in diagnosis

This paper proposes a way of incorporating fuzzy temporal reasoning within diagnostic reasoning. Disorders are described as an evolving set of necessa ry and possible manifestations. Ill-known moments in time, e.g., when a man ifestation should start or end, are modeled by fuzzy intervals, which are a lso used to model the elapsed time between events, e.g., the beginning of a manifestation and its end. Patient information about the intensity and tim es in which manifestations started and ended are also modeled using fuzzy s ets. The paper discusses many measures of consistency between the patient's data and the disorder model, and defines when the manifestations of the pa tient can be explained by a disorder. This work also discusses related issu es such as the intensity of manifestations and the speed in which the disor der is evolving, given the patient's data, and how to use that information to make predictions about future and past events.