Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
Propagation of Uncertainty from Systematic Error
Mechanistic Models: Compartment Models in Individual and Population Analysis
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches
您也可能阅读
通过共同作者、期刊和引用图与本文相关的文章。
Youngsoo Baek1, Wilkins Aquino2, Sayan Mukherjee1,3,4,5
1Department of Statistical Science, Duke University, Durham, NC, United States of America.
我们引入了一个新的概率框架,用于解决基于偏微分方程 (PDE) 的反向问题,而不需要假设概率模型. 这种方法增强了不确定性量化和复杂应用的模型选择.
科学领域:
背景情况:
研究的目的:
主要方法:
主要成果:
结论: