A Novel Selection Model of Surgical Treatments for Early Gastric Cancer Patients Based on Heterogeneous Multicriteria Group Decision-Making

被引:17
作者
Li, Dan-Ping [1 ]
He, Ji-Qun [2 ]
Cheng, Peng-Fei [1 ,3 ]
Wang, Jian-Qiang [3 ,4 ]
Zhang, Hong-Yu [3 ,4 ]
机构
[1] Hunan Univ Sci & Technol, Sch Business, Xiangtan 411201, Peoples R China
[2] Cent South Univ, Xiangya Hosp, Changsha 410008, Hunan, Peoples R China
[3] Hunan Engn Res Ctr Intelligent Decis Making & Big, Xiangtan 411201, Peoples R China
[4] Cent South Univ, Sch Business, Changsha 410083, Hunan, Peoples R China
来源
SYMMETRY-BASEL | 2018年 / 10卷 / 06期
基金
中国国家自然科学基金;
关键词
early gastric cancer surgery; selection model of surgical treatment; TOPSIS method; heterogeneous; MCGDM; RISK ANALYSIS; TOPSIS; INFORMATION; MORTALITY; EXTENSION; SETS;
D O I
10.3390/sym10060223
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Gastric cancer results in malignant tumors with high morbidity and mortality, and seriously affects the health and life quality of patients. Early detection and appropriate treatment for early-stage gastric cancer patients are very helpful to reducing the recurrence rate and improving survival rates. Hence, the selection of a suitable surgical treatment is an important part. At present, surgical treatment selection has been researched in numerous studies, but there is no study integrating fuzzy decision-making theory with quantitative analysis, considering the patient's conditions with other relative conditions, and which can handle multisource heterogeneous information at the same time. Hence, this paper proposes a novel selection model of surgical treatments for early gastric cancer based on heterogeneous multiple-criteria group decision-making (MCGDM), which is helpful to selecting the most appropriate surgery in the case of asymmetric information between doctors and patients. Subjective and objective criteria are comprehensively taken into account in the index system of the selection model for early gastric cancer, which combines fuzzy theory with quantitative data analysis. Moreover, the evaluation information obtained from the patient's conditions, the surgery, and the hospital's medical status, etc., including crisp numbers, interval numbers, neutrosophic numbers, and probabilistic linguistic labels, is more complete and real, so the surgical treatment selection is accurate and reliable. Furthermore, the technique for order of preference by similarity to ideal solution (TOPSIS) method is employed to solve the prioritization of early gastric cancer surgical treatments. Finally, an empirical study of surgical treatment selection for early gastric cancer surgery is conducted, and the results of sensitivity analysis and comparative analysis suggest that the proposed selection model of surgical treatments for early gastric cancer patients is reliable and effective.
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页数:29
相关论文
共 55 条
  • [1] Fuzzy TOPSIS Multi-Criteria Decision Analysis Applied to Karun Reservoirs System
    Afshar, Amin
    Marino, Miguel A.
    Saadatpour, Motahareh
    Afshar, Abbas
    [J]. WATER RESOURCES MANAGEMENT, 2011, 25 (02) : 545 - 563
  • [2] A neutrosophic recommender system for medical diagnosis based on algebraic neutrosophic measures
    Ali, Mumtaz
    Le Hoang Son
    Nguyen Dang Thanh
    Nguyen Van Minh
    [J]. APPLIED SOFT COMPUTING, 2018, 71 : 1054 - 1071
  • [3] [Anonymous], 2005, COMPUT SCI
  • [4] [Anonymous], 2017, SYMMETRY BASEL, DOI DOI 10.3390/SYM9080156
  • [5] [Anonymous], J MINIM INVASIVE GYN
  • [6] [Anonymous], 1992, Fuzzy Multiple Attribute Decision Making: Methods and Applications
  • [7] [Anonymous], 1981, MULTIPLE ATTRIBUTES
  • [8] [Anonymous], HAMMING LIKE DISTANC
  • [9] The extended QUALIFLEX method for multiple criteria decision analysis based on interval type-2 fuzzy sets and applications to medical decision making
    Chen, Ting-Yu
    Chang, Chien-Hung
    Lu, Jui-fen Rachel
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2013, 226 (03) : 615 - 625
  • [10] A direct interval extension of TOPSIS method
    Dymova, Ludmila
    Sevastjanov, Pavel
    Tikhonenko, Anna
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2013, 40 (12) : 4841 - 4847