Cargando…
Bayesian Data Assimilation to Support Informed Decision Making in Individualized Chemotherapy
An essential component of therapeutic drug/biomarker monitoring (TDM) is to combine patient data with prior knowledge for model‐based predictions of therapy outcomes. Current Bayesian forecasting tools typically rely only on the most probable model parameters (maximum a posteriori (MAP) estimate). T...
Autores principales: | Maier, Corinna, Hartung, Niklas, de Wiljes, Jana, Kloft, Charlotte, Huisinga, Wilhelm |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7080550/ https://www.ncbi.nlm.nih.gov/pubmed/31905420 http://dx.doi.org/10.1002/psp4.12492 |
Ejemplares similares
-
Reinforcement learning and Bayesian data assimilation for model‐informed precision dosing in oncology
por: Maier, Corinna, et al.
Publicado: (2021) -
A continued learning approach for model‐informed precision dosing: Updating models in clinical practice
por: Maier, Corinna, et al.
Publicado: (2021) -
Cell‐level systems biology model to study inflammatory bowel diseases and their treatment options
por: Stübler, Sabine, et al.
Publicado: (2023) -
Towards Model-Informed Precision Dosing of Voriconazole: Challenging Published Voriconazole Nonlinear Mixed-Effects Models with Real-World Clinical Data
por: Kluwe, Franziska, et al.
Publicado: (2023) -
Role of renal function in risk assessment of target non-attainment after standard dosing of meropenem in critically ill patients: a prospective observational study
por: Ehmann, Lisa, et al.
Publicado: (2017)