Design of a hybrid neuro-fuzzy decision-support system with a heterogeneous structure
Michael Negnevitsky · 2005
This paper describes the design of a hybrid neuro-fuzzy system for diagnosing myocardial perfusion from cardiac images. The model described in this project has a heterogeneous structure - the neural network and fuzzy system work as independent components. When a new case is presented to the diagnostic system, the trained neural network determines inputs to the fuzzy system. Then the fuzzy system using predefined fuzzy sets and fuzzy rules, maps the given inputs to an output, and thereby obtains the risk of a heart attack.