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Open Access Journal Article

Fuzzy Logic-Based Approaches for Medical Diagnosis Systems

by David Brown 1,*
1
David Brown
*
Author to whom correspondence should be addressed.
TASC  2022, 27; 4(1), 27; https://doi.org/10.69610/j.tasc.20220316
Received: 27 January 2022 / Accepted: 23 February 2022 / Published Online: 16 March 2022
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Abstract

This paper explores the utilization of fuzzy logic in the development of advanced medical diagnosis systems. Fuzzy logic, as a form of many-valued logic derived from fuzzy set theory, offers a unique approach to handling uncertainty, vagueness, and ambiguity in decision-making processes. In the healthcare sector, these attributes are particularly valuable as medical diagnoses often involve subjective judgments and uncertain clinical data. The abstract delves into the mechanisms through which fuzzy logic can enhance the accuracy and efficiency of diagnostic systems. It discusses various fuzzy logic-based approaches, including fuzzy expert systems, fuzzy neural networks, and hybrid systems, which integrate fuzzy logic with other AI techniques. The paper further analyzes the advantages and limitations of these methods and presents a comparative study of their performance. Additionally, it highlights the practical implementation of fuzzy logic in real-world medical diagnostic systems and discusses future directions for research in this field.

Keywords: Fuzzy logic, Medical diagnosis, Expert systems, Neural networks, Uncertainty handling.;
Copyright: © 2022 by Brown. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (Creative Commons Attribution 4.0 International License). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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ACS Style
Brown, D. Fuzzy Logic-Based Approaches for Medical Diagnosis Systems. Transactions on Applied Soft Computing, 2022, 4, 27. https://doi.org/10.69610/j.tasc.20220316
AMA Style
Brown D. Fuzzy Logic-Based Approaches for Medical Diagnosis Systems. Transactions on Applied Soft Computing; 2022, 4(1):27. https://doi.org/10.69610/j.tasc.20220316
Chicago/Turabian Style
Brown, David 2022. "Fuzzy Logic-Based Approaches for Medical Diagnosis Systems" Transactions on Applied Soft Computing 4, no.1:27. https://doi.org/10.69610/j.tasc.20220316
APA style
Brown, D. (2022). Fuzzy Logic-Based Approaches for Medical Diagnosis Systems. Transactions on Applied Soft Computing, 4(1), 27. https://doi.org/10.69610/j.tasc.20220316

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