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Neutrosophic and Information Fusion

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Online: 2836-7863
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Continuous publication

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Open access journal. All articles are freely available online with no APC.

Neutrosophic and Information Fusion
Full Length Article

Volume 5Issue 1PP: 25–36 • 2025

Neutrosophic Cosine Similarity Fusion with CRITIC-Weighted Ideal Profile Matching for Multi-Attribute Diabetes Risk Stratification: Evidence from the CDC BRFSS 2021 Dataset

Dae Yu Kim 1* ,
Jeong Chan Park 2
1Department of Electrical Engineering, Inha University, Korea
2Central Asian University, Tashkent, Uzbekistan
* Corresponding Author.
Received: December 03, 2024 Accepted: February 02, 2025

Abstract

Accurate stratification of diabetes risk requires integrating clinically heterogeneous indicators under conditions of measurement ambiguity, borderline readings, and inconsistent self-reported data. This paper introduces a Neutrosophic Cosinesimilarity with CRITIC-weighted ideal-profile matching (NCRS-CRITIC) framework that maps each patient record to an ideal disease profile and an ideal healthy profile simultaneously, using neutrosophic truth, indeterminacy, and falsity membership functions. The degree of closeness to each profile is measured through a weighted neutrosophic cosine similarity, where feature weights are derived via the CRITIC (CRIteria Importance Through Intercriteria Correlation) method— capturing both the discriminative variability and the inter-feature correlation structure objectively. A relative closeness coefficient (RC) aggregates dual-profile similarity into a scalar risk score that respects both the evidence for and against disease simultaneously. Experiments on a balanced 2000-instance subset of the CDC Behavioral Risk Factor Surveillance System (BRFSS) 2021 Diabetes Health Indicators Dataset achieve an area under the ROC curve (AUC) of 0.869 and accuracy of 79.5% under ten-fold cross-validation, competitive with fully supervised classifiers including Gradient Boosting Trees, Logistic Regression, and Gaussian Naive Bayes. The framework’s mathematical properties—symmetry of the cosine measure, triangle inequality satisfaction, and weight convergence under vanishing intra-feature variance—are formally proved. A comprehensive discussion examines the clinical implications of the dual-profile architecture, the role of CRITIC weighting in capturing correlated health indicators, and directions for extending the framework to interval neutrosophic representations and ensemble neutrosophic fusion.

Keywords

Neutrosophic sets Cosine similarity information fusion CRITIC weighting Ideal solution Diabetes prediction CDC BRFSS Mlti-attribute decision making Uncertainty modelling Pattern recognition

References

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[7] Teboul, A. (2023). CDC diabetes health indicators dataset. Kaggle / UCI Machine Learning Repository. Derived from CDC BRFSS 2015 health indicators data. https://www.kaggle.com/datasets/alexteboul/ diabetes-health-indicators-dataset. Mirrored by the UCI Machine Learning Repository. Accessed 2024.

 

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Kim, Dae Yu, Park, Jeong Chan. "Neutrosophic Cosine Similarity Fusion with CRITIC-Weighted Ideal Profile Matching for Multi-Attribute Diabetes Risk Stratification: Evidence from the CDC BRFSS 2021 Dataset." Neutrosophic and Information Fusion, vol. Volume 5, no. Issue 1, 2025, pp. 25–36. DOI: https://doi.org/10.54216/NIF.050103
Kim, D., Park, J. (2025). Neutrosophic Cosine Similarity Fusion with CRITIC-Weighted Ideal Profile Matching for Multi-Attribute Diabetes Risk Stratification: Evidence from the CDC BRFSS 2021 Dataset. Neutrosophic and Information Fusion, Volume 5(Issue 1), 25–36. DOI: https://doi.org/10.54216/NIF.050103
Kim, Dae Yu, Park, Jeong Chan. "Neutrosophic Cosine Similarity Fusion with CRITIC-Weighted Ideal Profile Matching for Multi-Attribute Diabetes Risk Stratification: Evidence from the CDC BRFSS 2021 Dataset." Neutrosophic and Information Fusion Volume 5, no. Issue 1 (2025): 25–36. DOI: https://doi.org/10.54216/NIF.050103
Kim, D., Park, J. (2025) 'Neutrosophic Cosine Similarity Fusion with CRITIC-Weighted Ideal Profile Matching for Multi-Attribute Diabetes Risk Stratification: Evidence from the CDC BRFSS 2021 Dataset', Neutrosophic and Information Fusion, Volume 5(Issue 1), pp. 25–36. DOI: https://doi.org/10.54216/NIF.050103
Kim D, Park J. Neutrosophic Cosine Similarity Fusion with CRITIC-Weighted Ideal Profile Matching for Multi-Attribute Diabetes Risk Stratification: Evidence from the CDC BRFSS 2021 Dataset. Neutrosophic and Information Fusion. 2025;Volume 5(Issue 1):25–36. DOI: https://doi.org/10.54216/NIF.050103
D. Kim, J. Park, "Neutrosophic Cosine Similarity Fusion with CRITIC-Weighted Ideal Profile Matching for Multi-Attribute Diabetes Risk Stratification: Evidence from the CDC BRFSS 2021 Dataset," Neutrosophic and Information Fusion, vol. Volume 5, no. Issue 1, pp. 25–36, 2025. DOI: https://doi.org/10.54216/NIF.050103
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