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Machine Learning for Treatment Assignment: Improving Individualized Risk Attribution
Clinical studies model the average treatment effect (ATE), but apply this population-level effect to future individuals. Due to recent developments of machine learning algorithms with useful statistical guarantees, we argue instead for modeling the individualized treatment effect (ITE), which has be...
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| Publicat a: | AMIA Annu Symp Proc |
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| Autors principals: | , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
American Medical Informatics Association
2015
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4765638/ https://ncbi.nlm.nih.gov/pubmed/26958271 |
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