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- W2023548081 abstract "In this paper, a model based on the adaptive network-based fuzzy inference system (ANFIS) with the improved genetic algorithm is used to predict the adequacy of vancomycin regimen. The improved genetic algorithm, i.e., hybrid Taguchi-genetic algorithm (HTGA), is applied in the ANFIS to simultaneously find the optimal premise and consequent parameters and a total output layer parameter by directly maximizing the training accuracy performance criterion. Experimental results show that the HTGA-based ANFIS model outperforms the logistic regression model in terms of prediction accuracy. Therefore, this study demonstrates the feasibility of applying the HTGA-based ANFIS as the mechanism of the decision support systems for the adequacy of vancomycin regimen for the patients based on clinical databases." @default.
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- W2023548081 date "2011-09-01" @default.
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- W2023548081 title "An ANFIS-based model for predicting adequacy of vancomycin regimen using improved genetic algorithm" @default.
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- W2023548081 doi "https://doi.org/10.1016/j.eswa.2011.04.109" @default.
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