Fuzzy mathematical models assist physicians in making superior choices because of the ambiguity and inaccuracy of patient entries. This study aims at improving the performance of medical accuracy through the incorporation of fuzzy logic into healthcare decision support systems. The following paper employed clinical factors in making fuzzy inference system which was experimented on real patient datasets. The findings reveal that treatment conceptions are more credible compared to conventional conceptions. The findings support the application of fuzzy-based systems in more complicated clinical assessments, particularly in case there is uncertainty or grey zone in the medical scenario.