Cargando…
Identification of high‐dimensional omics‐derived predictors for tumor growth dynamics using machine learning and pharmacometric modeling
Pharmacometric modeling can capture tumor growth inhibition (TGI) dynamics and variability. These approaches do not usually consider covariates in high‐dimensional settings, whereas high‐dimensional molecular profiling technologies (“omics”) are being increasingly considered for prediction of antica...
Autores principales: | Zwep, Laura B., Duisters, Kevin L. W., Jansen, Martijn, Guo, Tingjie, Meulman, Jacqueline J., Upadhyay, Parth J., van Hasselt, J. G. Coen |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8099445/ https://www.ncbi.nlm.nih.gov/pubmed/33792207 http://dx.doi.org/10.1002/psp4.12603 |
Ejemplares similares
-
Identification of antibiotic collateral sensitivity and resistance interactions in population surveillance data
por: Zwep, Laura B, et al.
Publicado: (2021) -
The status of pharmacometrics in pregnancy: highlights from the 3(rd) American conference on pharmacometrics
por: van Hasselt, J G Coen, et al.
Publicado: (2012) -
Metaheuristics for pharmacometrics
por: Kim, Seongho, et al.
Publicado: (2021) -
Model Evaluation of Continuous Data Pharmacometric Models: Metrics and Graphics
por: Nguyen, THT, et al.
Publicado: (2017) -
Pharmacometrics and Machine Learning Partner to Advance Clinical Data Analysis
por: Koch, Gilbert, et al.
Publicado: (2020)