Temporal characterization of ill-known diseases

In the identification of unknown diseases the temporal evolution is one of the most important aspects. Very often information about a new disease is imprecise and vague, due to the fact that the disease itself is hardly recognized by studying the symptoms of the patients. To this aim, we have applied a Fuzzy Temporal Reasoning system we have developed to the case of Severe Acute Respiratory Syndrome (SARS). The system is able to handle both qualitative and metric temporal knowledge affected by vagueness and uncertainty. In this preliminary work, we show how the fuzzy temporal framework allows us to represent temporal evolutions of symptoms in different patients thus making possible to deduce characteristic periods of an unknown disease such as SARS was.