Computational models of the artificial intelligence such as soft set theory have several applications. Parameterization reduction under soft set theory can be considered as a technique for medical decision making. One possible application is the decision making of patients suspected influenza. In this paper, we present the applicability of soft set theory for decision making of patients suspected influenza. The proposed technique is based on maximal supported objects by parameters. At this stage of the research, results are presented and discussed from a qualitative point of view against recent soft decision making techniques through an artificial dataset.
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