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An Interval Type-2 Fuzzy Similarity-Based MABAC Approach for Patient-Centered Care

Author

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  • Junhua Hu

    (School of Business, Central South University, Changsha 410083, China)

  • Panpan Chen

    (School of Business, Central South University, Changsha 410083, China)

  • Yan Yang

    (School of Business, Central South University, Changsha 410083, China)

Abstract

Patient-centered care is an essential part of the implementation of integrated medicine, integrating humanistic care into nursing services, enhancing communication between caregivers and patients, and providing personalized service to patients. Based on the similarity of interval type-2 fuzzy numbers (IT2FNs), a novel similarity-based methodology is presented for the selection of the most suitable medical treatment under a patient-centered environment. First, we propose a new similarity based on the geometric properties of interval type-2 fuzzy numbers and present a new property based on the center of gravity. Meanwhile, in order to better highlight the advantages of the proposed similarity, we selected 30 samples for comparative experiments. Second, considering the straightforward logic of the multi-attributive border approximation area comparison (MABAC) method, we extended it based on similarity to make the decision more accurate. Finally, a realistic patient-centered type-2 diabetes treatment selection problem is presented to verify the practicality and effectiveness of the proposed algorithm. A comparative analysis with existing methods is also described.

Suggested Citation

  • Junhua Hu & Panpan Chen & Yan Yang, 2019. "An Interval Type-2 Fuzzy Similarity-Based MABAC Approach for Patient-Centered Care," Mathematics, MDPI, vol. 7(2), pages 1-25, February.
    • Handle: RePEc:gam:jmathe:v:7:y:2019:i:2:p:140-:d:202816
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    References listed on IDEAS

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    1. Lee, Yin-Yang & Lin, Julia L., 2010. "Do patient autonomy preferences matter? Linking patient-centered care to patient-physician relationships and health outcomes," Social Science & Medicine, Elsevier, vol. 71(10), pages 1811-1818, November.
    2. Chen, Ting-Yu & Chang, Chien-Hung & Rachel Lu, Jui-fen, 2013. "The extended QUALIFLEX method for multiple criteria decision analysis based on interval type-2 fuzzy sets and applications to medical decision making," European Journal of Operational Research, Elsevier, vol. 226(3), pages 615-625.
    3. Neha Singh & Kirti Tyagi, 2017. "Ranking of services for reliability estimation of SOA system using fuzzy multicriteria analysis with similarity-based approach," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(1), pages 317-326, January.
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    Cited by:

    1. Yulia Shichkina & Mikhail Petrov & Fatkieva Roza, 2022. "Determination of Significant Parameters on the Basis of Methods of Mathematical Statistics, and Boolean and Fuzzy Logic," Mathematics, MDPI, vol. 10(7), pages 1-13, April.
    2. Shu-Rong Yan & Khalid A. Alattas & Mohsen Bakouri & Abdullah K. Alanazi & Ardashir Mohammadzadeh & Saleh Mobayen & Anton Zhilenkov & Wei Guo, 2022. "Generalized Type-2 Fuzzy Control for Type-I Diabetes: Analytical Robust System," Mathematics, MDPI, vol. 10(5), pages 1-20, February.
    3. Darko Božanić & Dragan Pamucar & Ibrahim Badi & Duško Tešić, 2023. "A decision support tool for oil spill response strategy selection: application of LBWA and Z MABAC methods," OPSEARCH, Springer;Operational Research Society of India, vol. 60(1), pages 24-58, March.

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