Fuzzy Rule based Expert System for Diagnosis of Lung Cancer

Lung cancer is the second most common cancer in both men and women in the world. The focus of this paper is to design a fuzzy rule based medical expert system for diagnosis of lung cancer. The proposed system consists of four modules: working memory, knowledge base, inference engine and user interface. The system takes the risk factors and symptoms of lung cancer in a two-step process and stores them as facts of the problem in working memory. Also domain expert knowledge is gathered to generate rules and stored in the rule base. The rule base consists of two different rule sets related to risk factors and symptoms of lung cancer respectively. Finally, type-2 fuzzy inference engine fires relevant rules under appropriate condition and provides the probability of disease as output of the system. The output of the system could act as a second opinion to assist the physicians. Also graphical user interface is presented to facilitate the communication between user and system.