In recent years Artificial Intelligence Techniques (AITs) have now highly increased in solving complex and critical problems of more uncertainties that occur in the process of the system. AITs, offer the possibility of designing intelligent mathematical models involving Fuzzy Logic (FL), Artificial Neural Network (ANN), Genetic Algorithm (GA), and as such. In this, Fuzzy set theory is a highly suitable and applicable basis for developing knowledge-based systems in medical fields for diagnosing diseases and predicting risk factors. Fuzzy Logic decides uncertainty, incomplete, vagueness, and flexible structure with the use of intuitive methods. Due to the advent of digitalization in the field of the medical diagnostic process, Fuzzy Logic is highly suitable to make the decisions for diagnosis and treatment of different diseases. This article mainly focuses on a review of the applications of Fuzzy Logic in the Application areas of Medicines like Heart Disease, Asthma, Cold and Flu, Malaria, Parkinson's Disease, Diabetic Disease, Tuberculosis, Breast Cancer, and COVID-19 as well.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.