A neurofuzzy-based expert system for disease diagnosis

This paper describes the development of a medical diagnosis expert system that can be used by physicians in their daily practices. Differential artificial intelligence techniques are incorporated into the expert system to best represent the various stages of the diagnosis process. A linear scoring system is used to represent the initial subjective analysis stage, while a rule-based fuzzy expert system is used to interpret lab tests and imaging studies to confirm final diagnosis. An actual example of patient walkthrough is used to demonstrate various computation steps from embedding the patient information to reaching the final diagnosis.