Towards the construction of intuitionistic fuzzy cognitive maps for medical decision making

FCMs are appropriate to explicitly encode the knowledge and experience accumulated on the operation of a complex system. Once constructed for a particular domain, an FCM allows a qualitative simulation of the system. In this paper, we investigate a first approach to introduce intuitionistic fuzzy logic into the construction process of FCMs for improved medical decision making. The theory of intuitionistic fuzzy sets provides a sound mathematical model suitable for modeling the imprecision that is inherent in real world problems. It is employed to the step where the fuzzy if-then rules are used for the determination of cause-effect relationships assigning linguistic weights among the concepts. The novel intuitionistic FCM proposed in this paper are implemented by introducing a factor of hesitancy into the weights of a standard FCM. This factor provides an additional cue on the cause-effect relationships among concepts. The results from its experimental evaluation on a medical decision making problem that is critical to patient safety, indicate its effectiveness and open perspectives for its general applicability.