A fuzzy temporal diagnosis algorithm and a hypothesis discrimination proposal

Abstract

Over the last decades, Artificial Intelligence has approached the decision support system design in medical domains by capturing the knowledge and configuring it in knowledge intensive software systems. Model-based diagnosis is one of the techniques which has produced the best results, such as diagnosis intelligent systems in the realm of medicine. In this domain, one of the key factors is the temporal dimension. This variable enormously complicates the design of such systems, and in particular the process of getting a reliable diagnosis solution. This paper presents a Diagnosis Abductive Algorithm based on Fuzzy Temporal Abnormal Model. This algorithm provides a solution for the above problem by the description of its dianosis explanation, allowing an approach based on the Possibility Theory for the evaluation of the diagnosis hypotheses. © Springer-Verlag Berlin Heidelberg 2005.