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A Machine-Learning Approach for Estimating Subgroup- and Individual-Level Treatment Effects: An Illustration Using the 65 Trial
Personalizing treatment recommendations or guidelines requires evidence about the heterogeneity of treatment effects (HTE). Machine-learning (ML) approaches can explore HTE by considering many covariates, including complex interactions between them. Causal ML approaches can avoid overfitting, which...
Autores principales: | Sadique, Zia, Grieve, Richard, Diaz-Ordaz, Karla, Mouncey, Paul, Lamontagne, Francois, O’Neill, Stephen |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9459357/ https://www.ncbi.nlm.nih.gov/pubmed/35607982 http://dx.doi.org/10.1177/0272989X221100717 |
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