It is observed that real world problems are usually tainted with uncertainty arises due to lack of knowledge, imprecision, partial information. To deal with such uncertainty Zadeh (1965) developed a tool, which is well known as FST. Basically, in real life situations, due to the imprecise nature of medical documents and uncertain information gathered for decision making requires the use of fuzzy. In FST, to each element of the universe of discourse a degree of membership between 0 and 1 is assigned. However, it is not always possible for a membership function of the type to precisely assign one point from [0,1] so it is more realistic to assign interval value. People believe that assigning an exact number to expert’s opinion is too restrictive and the assignment of an interval valued is more realistic (Gehrke et al., 1996). In such situations, IVFS can be considered as an extended version of FST. The concept of IVFS was first presented by Sambuc (1975) in his doctoral research (thesis) names as fuzzy set. Thereafter, an important generalization of FST has been made by Atanassov (1986) and termed IFS. IFS ascribe a membership degree and a non-membership degree separately in such a way that sum of the two degrees must not exceed one. It is observed that fuzzy sets are IFSs but converse is not necessarily correct. Later, Cuong and Kreinovich (2013) introduced PFS which is a direct extension of FST and IFS by incorporating the concept of positive, negative and neutral membership degree of an element.