A fuzzy rule-based system for cancer risk assessment

Cancer risk assessment is a crucial component of early detection and prevention strategies. This paper introduces an advanced Fuzzy Logic Control-Based System designed to intelligently evaluate cancer risk by processing multiple relevant factors. The proposed system utilizes fuzzy logic rules to seamlessly integrate key variables such as age, air pollution levels, alcohol consumption, chronic lung disease, and smoking habits. By employing a fuzzy inference system, this model provides a comprehensive and accurate prediction of cancer risk.