A multi-level fuzzy inference system for developing DSS based on clinical guidelines

Clinical Decision Support Systems (CDSSs) are typically based on clinical guidelines explicitly formalized in the form of rules for reproducing the physician´s decisionmaking process and, also, improving the efficiency of medical practices. With the aim of building CDSSs able to represent uncertainty existing in clinical guidelines and efficiently reason on a huge number of inter-connected rules, this paper presents a multi-level fuzzy inference system offering the following set of specifically-devised functionalities: (i) fuzzy rules can be organized in one or more groups of positive evidence rules, where each group is able to interact with other ones by properly chaining their conclusions; (ii) rules inside a group are independently processed and evaluated; (iii) each group of rules can be customized by means of a peculiar configuration for the inference; (iv) a fuzzy ELSE rule can be associated to a group for assembling all the negative evidence for a specific situation. A proof of concept scenario is finally given to describe how the proposed solution can be applied.