Intuitionistic Robust Fuzzy Matrix for the Diagnosis of Stress, Anxiety and Hypertension
DOI:
https://doi.org/10.23755/rm.v46i0.1087Keywords:
Fuzzy logic, fuzzy matrices, max-min principles, Robust, Intuitionistics.Abstract
The mathematical model given here attempts to improve precision
in the diagnosis of stress, anxiety, and hypertension using Intuitionistic
robust fuzzy matrix (IRFM). In practice, the imprecise nature
of medical documentation and the uncertainty of patient information
frequently do not provide the appropriate level of confidence in the
diagnosis. To that purpose, a novel method based on distinct fuzzy
matrices and fuzzy relations is devised, which makes use of the capabilities
of fuzzy logic in describing, understanding, and exploiting
facts and information that are unclear and lack clarity. With the assistance
of 30 doctors, a medical knowledge base is created during the
procedure. The model obtained 95.55%t accuracy in the diagnosis,
demonstrating its utility.
References
K. Adlassing. Fuzzy set theory in medical diagnosis. IEEE Transaction systems
Man Cybernetics, 16:260–265, 1986.
S. Elizabeth and Sujatha.L. Application of fuzzy membership matrix in medical
diagnosis and decision making. Applied Mathematical Sciences, 7:6297–6307,
S. Gupta. Statistical Methods. S. Chand and sons, New Delhi, 1976.
G. Klir and B. Yuan. Fuzzy Sets and Fuzzy Logic: Theory and Applications.
Prentice- Hall, address = New Jersey, 1995.
A. R. Meenakshi and K. M. An application of interval-valued fuzzy matrices in
medical diagnosis. International Journal of Mathematical Analysis, 5:1791–
, 2011.
T. R. A. V. Raich, V. and S. Dalal. Application of fuzzy matrix in the study of
diabetes. World Academy of Science, 56:22–28, 2009.
Ravi.J. Fuzzy graph and their applications: A review. International Journal for
Science and Advance Research in Technology, 8:107–111, 2022.
E. Sanchez. Inverse of fuzzy relations, application to possibility distribution and
medical diagnosis. Fuzzy Sets and Systems, 2:75–86, 1979.
K. Saravanan and J. Prasanna. Applications of fuzzy matrices in medicine. Global
Journal of Pure and Applied Mathematics, 2:80–84, 2016.
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