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Efficient augmentation and relaxation learning for individualized treatment rules using observational data
Individualized treatment rules aim to identify if, when, which, and to whom treatment should be applied. A globally aging population, rising healthcare costs, and increased access to patient-level data have created an urgent need for high-quality estimators of individualized treatment rules that can...
Autores principales: | Zhao, Ying-Qi, Laber, Eric B., Ning, Yang, Saha, Sumona, Sands, Bruce E. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6705615/ https://www.ncbi.nlm.nih.gov/pubmed/31440118 |
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