Abstract
Three-way decision models and their relative applications have received a great deal of research attention. Most of these models were constructed on the basis of decision-theoretic rough sets (DTRSs) and Bayesian decision theory, both of which ignore the risk preferences of decision-makers. To address this shortcoming, this paper constructs a novel TODIM method-based three-way decision model and demonstrates its use in the context of online diagnosis and medical treatment selection. This model combines information systems and DTRSs together to construct a hybrid information system. And it solves the problems in aggregating cost-loss information with different levels of importance by utilizing the power average operator. Furthermore, an extension of the TODIM method is proposed based on the novel possibility degree measurement considering the probability distribution of loss functions. To validate the reasonableness and effectiveness of our model, we give a series of simulation experiments related to treatment selection for a Good Doctor Online user infected with the common cold.
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This work was supported by the National Natural Science Foundation of China (Nos. 71371196 and 71210003).
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Hu, J., Yang, Y. & Chen, X. A Novel TODIM Method-Based Three-Way Decision Model for Medical Treatment Selection. Int. J. Fuzzy Syst. 20, 1240–1255 (2018). https://doi.org/10.1007/s40815-017-0320-3
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DOI: https://doi.org/10.1007/s40815-017-0320-3