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

Abstract

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.

A Multi-Criteria 2-Tuple Linguistic Group Decision-Making Method Based on TODIM for Cholecystitis Treatments Selection

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A Multi-Level Privacy-Preserving Approach to Hierarchical Data Based on Fuzzy Set Theory

“…Let U be the domain of a numerical attribute (for categorical attribute, a numerical attribute can be obtained according to the frequency of every value), and min and max be the minimum and maximum values in U, respectively. 4 , max], respectively, where a 3 = (min + max)/2, a 1 = min + (a 3 -min)/3, a 2 = min + 2(a 3 -min)/3, a 4 = a 3 + (max-a 3 )/3, a 5 = a 3 + 2(max-a 3 )/3. That is, a 1 , a 2 , a 3 , a 4 and a 5 uniformly divide the interval [min, max].…”

“…For example, for an equivalence class Q in a hierarchical data, we assume that the sensitive attribute of the root vertex in the class representative of Q is the cumulative GPA, whose value is {0.8, 1.6, 2.3, 2.7, 3.5, 3.9}, where the domain of the cumulative GPA is [0,4]. We can obtain the min = 0, max = 4, a 3 = 2, a 1 = 2/3, a 2 = 4/3, a 4 = 8/3 and a 5 = 10/3.…”

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“…With respect to the partial use of information in assessment [10], it is appropriate to apply historical financial information and fuzzy theory to describe assessment information about financial risk for companies. The assessment information from historical financial information of company mainly involves crisp numbers.…”