A New Distance Measure under Spherical Fuzzy Environment for Lung Cancer Risk Factors
DOI:
https://doi.org/10.2298/YJOR251015046RKeywords:
Spherical Fuzzy Numbers, Distance Measure, Risk factors, MCDM, COPRAS, DEMATEL, Lung cancer, Sensitivity AnalysisAbstract
Lung cancer remains one of the leading causes of cancer-related mortality worldwide, and its early detection and prevention are highly dependent on the identification of critical risk factors. To address the complexity and uncertainty inherent in expert judgment, this study introduces a novel spherical fuzzy distance measure for evaluating lung cancer risk factors. The proposed framework integrates the Decision-Making Trial and Evaluation Laboratory (DEMATEL) to capture interrelationships among the risk factors, while the COmplex PRoportional ASsessment (COPRAS) method is applied to rank their relative importance. To enhance the reliability of aggregated expert opinions, the Einstein aggregation operator is employed, offering a more flexible approach to handling fuzziness in decision-making data. Furthermore, a comprehensive sensitivity analysis was conducted to validate the robustness and stability of the results across different parameter variations. The findings not only highlight the most influential lung cancer risk factors but also demonstrate the superiority of the proposed spherical fuzzy distance measure in managing ambiguity and uncertainty in medical decision-making. This novel approach provides a valuable decision-support tool for healthcare professionals and policymakers to prioritise preventive strategies for lung cancer.
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