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A novel behavioral three-way decision model with application to the treatment of mild symptoms of COVID-19.
He, Shi-Fan; Wang, Ying-Ming; Pan, Xiaohong; Chin, Kwai-Sang.
Afiliação
  • He SF; Decision Sciences Institute, Fuzhou University, Fujian, 350108, China.
  • Wang YM; Department of Systems Engineering and Engineering Management, City University of Hong Kong, Hong Kong.
  • Pan X; Decision Sciences Institute, Fuzhou University, Fujian, 350108, China.
  • Chin KS; Decision Sciences Institute, Fuzhou University, Fujian, 350108, China.
Appl Soft Comput ; 124: 109055, 2022 Jul.
Article em En | MEDLINE | ID: mdl-35637858
The Coronavirus Disease 2019 (COVID-19) has popularized since late December 2019. In present, it is still highly transmissible and has severe impact on the public health and global economy. Due to the lack of specific drug and the appearance of different variants, the selection of the antiviral therapy to treat the patients with mild symptom is of vital importance. Hence, in this paper, we propose a novel behavioral Three-Way Decision (3WD) model and apply it to the medicine selection decision. First, a new relative utility function is constructed by considering the risk-aversion behavior and regret-aversion behavior of human beings. Second, based on the relative utility function, some new rules are defined to calculate the thresholds and conditional probabilities in 3WD and some corresponding theorems are explored and proved. Next, a new information fusion mechanism in the framework of evidential reasoning algorithm is developed. Then, the decision results are obtained based on the Bayesian decision procedure and the principle of maximum utility. Finally, an example with large-scale data set and an example about medicine selection for COVID-19 are provided to show the implementation process and effectiveness of the proposed method. Comparative analysis and sensitivity analysis are also performed to illustrate the superiority and the robustness of the current proposal.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Health_economic_evaluation / Prognostic_studies Idioma: En Revista: Appl Soft Comput Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Health_economic_evaluation / Prognostic_studies Idioma: En Revista: Appl Soft Comput Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China