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...

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Detalles Bibliográficos
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:
Research
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

Internet

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

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