Cargando…
Big Data Toolsets to Pharmacometrics: Application of Machine Learning for Time‐to‐Event Analysis
Additional value can be potentially created by applying big data tools to address pharmacometric problems. The performances of machine learning (ML) methods and the Cox regression model were evaluated based on simulated time‐to‐event data synthesized under various preset scenarios, i.e., with linear...
Autores principales: | Gong, Xiajing, Hu, Meng, Zhao, Liang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5944589/ https://www.ncbi.nlm.nih.gov/pubmed/29536640 http://dx.doi.org/10.1111/cts.12541 |
Ejemplares similares
-
Pharmacometrics and Machine Learning Partner to Advance Clinical Data Analysis
por: Koch, Gilbert, et al.
Publicado: (2020) -
Evaluation of machine learning methods for covariate data imputation in pharmacometrics
por: Bräm, Dominic Stefan, et al.
Publicado: (2022) -
SeqHBase: a big data toolset for family based sequencing data analysis
por: He, Min, et al.
Publicado: (2015) -
Big data made easy
:
a working guide to the complete Hadoop toolset
por: Frampton, Michael
Publicado: (2015) -
Heterogeneous treatment effect analysis based on machine‐learning methodology
por: Gong, Xiajing, et al.
Publicado: (2021)