Temporal-based medical diagnoses using a Fuzzy Temporal Reasoning System

We apply the Fuzzy Temporal Constraint System we have developed to the case of SARS (Severe Acute Respiratory Syndrome). The idea is to characterize the temporal evolution of the symptoms of this ill-known disease by modelling patients’ data in a Fuzzy Temporal Constraint Network. We discuss how the system is able to manage both fuzzy qualitative and metric constraints allowing to represent in a flexible manner the symptoms of different patients. In this way it is possible to deduce characteristic periods of an ill-known disease such as SARS was. A new user interface is included into the architecture of the System.

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