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- W3094344238 abstract "This paper extends the classical pharmacokinetic model from a deterministic framework to an uncertain one to rationally explain various noises, and applies theory of uncertain differential equations to analyzing this model. It is proved that the inverse uncertainty distribution for the drug concentration can be obtained by a system of ordinary differential equations. Based on this result, properties such as uncertainty distributions, expected values, and confidence intervals for some essential pharmacokinetic indexes are obtained. For unknown parameters in the uncertain pharmacokinetic model, generalized moments estimations are given. A numerical example compares our methods with the deterministic method, and illustrates the effectiveness and rationality of our methods. Furthermore, the proposed methods are applied to a real dataset. Finally, the paradox of stochastic pharmacokinetic model is pointed out." @default.
- W3094344238 created "2020-10-29" @default.
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- W3094344238 date "2021-03-01" @default.
- W3094344238 modified "2023-10-17" @default.
- W3094344238 title "Pharmacokinetic model based on multifactor uncertain differential equation" @default.
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- W3094344238 doi "https://doi.org/10.1016/j.amc.2020.125722" @default.
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