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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...
Αποθηκεύτηκε σε:
| Τόπος έκδοσης: | AMIA Annu Symp Proc |
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| Κύριοι συγγραφείς: | , , , , |
| Μορφή: | Artigo |
| Γλώσσα: | Inglês |
| Έκδοση: |
American Medical Informatics Association
2015
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| Θέματα: | |
| Διαθέσιμο Online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4765638/ https://ncbi.nlm.nih.gov/pubmed/26958271 |
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