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 necessary and possible manifestations. Ill-known moments in time, e.g., when a manifestation should start or end, are modeled by fuzzy intervals, which are also used to model the elapsed time between events, e.g., the beginning of a manifestation and its end. Patient information about the intensity and times in which manifestations started and ended are also modeled using fuzzy sets. The paper discusses many measures of consistency between the patient/s data and the disorder model, and defines when the manifestations of the patient can be explained by a disorder. This work also discusses related issues such as the intensity of manifestations and the speed in which the disorder is evolving, given the patient's data, and how to use that information to make predictions about future and past events.

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