The review aims at providing current state of evidence in the field of medicine with fuzzy logic for diagnosing diseases. Literature reveals that fuzzy logic has been used effectively in medicine. Different types of methodologies have been applied to diagnose the diseases based on symptoms, historical and clinical data of an individual. Increase in the number of recent applications of medicine with fuzzy-logic is an indication of growing popularity of fuzzy systems. Fuzzy intelligent systems developed during 2007-2018 have been studied to explore various techniques applied for disease prediction. In the traditional approach, a physician is required to diagnose disease based on historical and clinical data but the intelligent system will help physicians as well as individuals to detect disease at any location of the world. The studies of various fuzzy logic systems and classified fuzzy logic applications in the field of diabetes, iris, heart, breast cancer, dental, cholera, brain tumor, liver, asthma, viral, parkinson, lung, kidney, huntington and chest diseases have been included in the review. This study indicates all the benefits of the fuzzy logic to the society and direction to tackle the diseases that still need software for their accurate detection. Further, different case studies for celiac disease have been reported earlier. The current review aims at exploring the future direction for fuzzy methodologies and domain on celiac disease.
Keywords: ANFIS; Back-propagation; Celiac disease; Fuzzy logic; Neural networks.
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