These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
7. Maximum likelihood estimation of a time-inhomogeneous stochastic differential model of glucose dynamics. Picchini U; Ditlevsen S; De Gaetano A Math Med Biol; 2008 Jun; 25(2):141-55. PubMed ID: 18504247 [TBL] [Abstract][Full Text] [Related]
8. Stochastic differential equations as a tool to regularize the parameter estimation problem for continuous time dynamical systems given discrete time measurements. Leander J; Lundh T; Jirstrand M Math Biosci; 2014 May; 251():54-62. PubMed ID: 24631177 [TBL] [Abstract][Full Text] [Related]
9. Mixed Effects Modeling Using Stochastic Differential Equations: Illustrated by Pharmacokinetic Data of Nicotinic Acid in Obese Zucker Rats. Leander J; Almquist J; Ahlström C; Gabrielsson J; Jirstrand M AAPS J; 2015 May; 17(3):586-96. PubMed ID: 25693487 [TBL] [Abstract][Full Text] [Related]
10. Predictive performance for population models using stochastic differential equations applied on data from an oral glucose tolerance test. Møller JB; Overgaard RV; Madsen H; Hansen T; Pedersen O; Ingwersen SH J Pharmacokinet Pharmacodyn; 2010 Feb; 37(1):85-98. PubMed ID: 20013304 [TBL] [Abstract][Full Text] [Related]
11. A stochastic deconvolution method to reconstruct insulin secretion rate after a glucose stimulus. Sparacino G; Cobelli C IEEE Trans Biomed Eng; 1996 May; 43(5):512-29. PubMed ID: 8849464 [TBL] [Abstract][Full Text] [Related]
12. Reconstructing insulin secretion rate after a glucose stimulus by an improved stochastic deconvolution method. Pillonetto G; Sparacino G; Cobelli C IEEE Trans Biomed Eng; 2001 Nov; 48(11):1352-4. PubMed ID: 11686635 [TBL] [Abstract][Full Text] [Related]
13. Inference for nonlinear dynamical systems. Ionides EL; Bretó C; King AA Proc Natl Acad Sci U S A; 2006 Dec; 103(49):18438-43. PubMed ID: 17121996 [TBL] [Abstract][Full Text] [Related]
14. Investigations of a compartmental model for leucine kinetics using non-linear mixed effects models with ordinary and stochastic differential equations. Berglund M; Sunnåker M; Adiels M; Jirstrand M; Wennberg B Math Med Biol; 2012 Dec; 29(4):361-84. PubMed ID: 21965323 [TBL] [Abstract][Full Text] [Related]
15. Implementation of non-linear mixed effects models defined by fractional differential equations. Kaikousidis C; Dokoumetzidis A J Pharmacokinet Pharmacodyn; 2023 Aug; 50(4):283-295. PubMed ID: 36944853 [TBL] [Abstract][Full Text] [Related]
16. A review on estimation of stochastic differential equations for pharmacokinetic/pharmacodynamic models. Donnet S; Samson A Adv Drug Deliv Rev; 2013 Jun; 65(7):929-39. PubMed ID: 23528446 [TBL] [Abstract][Full Text] [Related]
17. REML estimation of variance parameters in nonlinear mixed effects models using the SAEM algorithm. Meza C; Jaffrézic F; Foulley JL Biom J; 2007 Dec; 49(6):876-88. PubMed ID: 17638294 [TBL] [Abstract][Full Text] [Related]
18. Global identifiability of nonlinear models of biological systems. Audoly S; Bellu G; D'Angiò L; Saccomani MP; Cobelli C IEEE Trans Biomed Eng; 2001 Jan; 48(1):55-65. PubMed ID: 11235592 [TBL] [Abstract][Full Text] [Related]
19. Application of an NLME-Stochastic Deconvolution Approach to Level A IVIVC Modeling. Kakhi M; Suarez-Sharp S; Shepard T; Chittenden J J Pharm Sci; 2017 Jul; 106(7):1905-1916. PubMed ID: 28341596 [TBL] [Abstract][Full Text] [Related]
20. Modeling of pharmacokinetic systems using stochastic deconvolution. Kakhi M; Chittenden J J Pharm Sci; 2013 Dec; 102(12):4433-43. PubMed ID: 24174399 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]