Contribution of machine learning to tumor growth inhibition modeling for hepatocellular carcinoma patients under Roblitinib (FGF401) drug treatment

Machine learning (ML) opens new perspectives in identifying predictive factors of efficacy among a large number of patients’ characteristics in oncology studies. The objective of this work was to combine ML with population pharmacokinetic/pharmacodynamic (PK/PD) modeling of tumor growth inhibition t...

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Detalles Bibliográficos
Autores principales: Wilbaux, Mélanie, Demanse, David, Gu, Yi, Jullion, Astrid, Myers, Andrea, Katsanou, Vasiliki, Meille, Christophe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9381917/
https://www.ncbi.nlm.nih.gov/pubmed/35728123
http://dx.doi.org/10.1002/psp4.12831

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9381917/
https://www.ncbi.nlm.nih.gov/pubmed/35728123
http://dx.doi.org/10.1002/psp4.12831

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