Development of Celiac Disease Fuzzy Logic Probabilistic System Based on Symptomatic Study

Abstract

newline The computational science in concoction with statistics has boosted new avenues of the newlinehealthcare monitoring system for the progress of mankind. This integration has attained newlinethe pinnacle of success in the present era for celiac patients as well as in other healthcare newlinedomains. The healthcare monitoring systems predict the diseases at an earlier stage, newlinewhich is challenging and necessitates to be executed precisely. In the recent era, celiac newlinedisease is considered one of the foremost chronic disorders in humans all over the newlineworld. Every researcher or physician suggested that a gluten-free diet is a unique way newlineto tackle the celiac disease, but identifying the celiac patient is a very cumbersome task. newlineThe present study reveals that various computational methodologies are present for newlinediagnosing chronic diseases based on patient s symptoms, historical and clinical data newlineviz. data mining, machine learning, fuzzy logic, soft computing, etc. The literature newlineexplicates that assimilation of machine learning and fuzzy logic has accomplished great newlinesuccess in healthcare monitoring or disease detection systems. The last four decades newlinebestow the dynamism of fuzzy logic in the healthcare monitoring system to predict newlinediseases at the earliest viz. brain tumor, heart, liver, iris, viral infection, parkinson, newlinebreast cancer, asthma, huntington, kidney, chest diseases, etc. It is prudent to develop newlinehealth monitoring systems with ambivalent symptoms through a fuzzy database newlineembracing fuzzy if-then rules.