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Traditional approaches based on algorithms are not feasible for solving detection of diseases throughout the world. Fuzzy Logic becomes more and more popular for diagnosing diseases based on different parameters and methodologies. This paper represents the literature review of articles in fuzzy logic to deal with various medical applications for last decade (2008-2018)because of identified different methodologies developed in this timeperiod. On the basis of different fuzzy applications in medical field, this article focused on eight common medical issues like heart disease, asthma disease, liver disease, breast cancer, Parkinson disease, cholera, dental and diabetes disease. Based on these different medical applications, the basic objective is to explore and implement fuzzy logic in existing and different domains in future.

The need for the proposed system mounts due to expensive clinical cost, the prolonged period of Genetic testing and especially painful for an individual to perform all certain clinical tests to diagnose celiac disease. With this proposed method, an individual can foretell celiac disease by just input crisp values of varied symptoms using fuzzy logic. A case study was conducted using a questionnaire procedure to obtain out the requisite symptoms in Amritsar, Punjab on 700 individuals; having 303 females and 393 males. So, the proposed system will be implemented using Mamdani Model and forms the prediction output practicing de-fuzzification when correlated with computed values produced optimum correctness. The proposed system will have a disease prediction of 96.11% accuracy according to the input values given by an individual to authenticate the celiac disease. The proposed system will provide a fruitful outcome for individuals and physicians for celiac disease disclosure in few seconds without any painful testing strategy.

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