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Aiding in Prognosis of Fibromyalgia Syndrome Utilizing MCDM TOPSIS Method in Fusion With Fuzzy Logic
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Author(s): Raghavendra M. Devadas (Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, India), Vani Hiremani (Symbiosis Institute of Technology, Symbiosis International University (Deemed), India)and Praveen Gujjar J. (Faculty of Management Studies, Jain University (Deemed), India)
Copyright: 2024
Pages: 26
Source title:
Ubiquitous Computing and Technological Innovation for Universal Healthcare
Source Author(s)/Editor(s): Arumugam Suresh Kumar (Jain University (Deemed), India), Geetha Ganesan (Jain University (Deemed), India), Ramesh Sekaran (Jain University (Deemed), India), Batri Krishnan (Jain University (Deemed), India)and N. V. Kousik (Arden University, UK)
DOI: 10.4018/979-8-3693-2268-0.ch006
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Abstract
The study addresses the complexity of Fibromyalgia syndrome (FMS) by integrating multi-criteria decision-making (MCDM) TOPSIS with fuzzy logic for accurate prognosis. A comprehensive set of criteria, including clinical, psychological, and physiological factors, is employed. Fuzzy logic models uncertainties and subjective expert opinions. The method systematically evaluates and ranks FMS prognoses, contributing to transparency in decision-making. Incorporating sensitivity analysis with small variations enhances reliability. Considering symptoms, patients, and expert ratings, the study identifies patient 5 as more likely to have FMS (closeness coefficient 0.881), while patient 1 is less prone (closeness coefficient 0.088).
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