Fuzzy decision making for medical diagnosis using arithmetic of generalised parabolic fuzzy numbers

In medical diagnosis, generally uncertainty (vagueness or imprecision) arises due to patients vague linguistic expression of their problems to medical experts. Furthermore, some sort of uncertainty may occur due to deficiencies in lab experiments and human error. To deal such uncertain situation, fuzzy set theory is explored. It is observed that these types of uncertainty may be reduced by further study and based on the nature of uncertainty or available data different types of fuzzy sets exist. In this paper, parabolic fuzzy number is taken into consideration for modeling uncertainty. Then, arithmetic of generalized parabolic fuzzy numbers (GPFNs) is studied first along with ranking of generalised trapezoidal parabolic fuzzy numbers (GTPFNs). After that, shortcomings of existing approach have been discussed. Finally, a decision making for medical diagnosis has been carried out using the proposed arithmetic and ranking approach as well. For this purpose, a list of patients, symptoms and based on symptoms a set of diseases are prepared. Then, patient–symptoms and symptoms–disease relationships are established. It is observed that the proposed model can identify the exact solution of the problems.