Abstract: Cancer disease diagnosis is difficult and needs higher level of expertise. Artificial Intelligence helps to solve the problem in Medical Expert System domain as expert people do. In the existing system, Fuzzy logic is used in medical expert system. This system is agroup of membership functions or rules and tilting toward multi-optional processing. Thiscreates confusion and gives a non-fixedresult which does not satisfy the user. The proposed system improve the performance of medical expert system by crisp logic, The Crisp Expert System defines imprecise knowledge and offers a linguistic concept with better approximation to medical condition. Crisp logic only permits conclusion which are either yes or no, there are also propositions with variables answers. The input variables their description value associated Crisp Sets and their indicator function indicates the membership of variables. The mathematical model developed is the pioneer attempt to predict the risk of Lung cancer disease and used to compare the performance of crisp expert system.
Keywords: Artificial Intelligence, Medical Expert System, Crisp Logic, Indicator Function, Boolean Logic.