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Reflection on modern methods: generalized linear models for prognosis and intervention—theory, practice and implications for machine learning
Prediction and causal explanation are fundamentally distinct tasks of data analysis. In health applications, this difference can be understood in terms of the difference between prognosis (prediction) and prevention/treatment (causal explanation). Nevertheless, these two concepts are often conflated...
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| Publicat a: | Int J Epidemiol |
|---|---|
| Autors principals: | , , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Oxford University Press
2020
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7825942/ https://ncbi.nlm.nih.gov/pubmed/32380551 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/ije/dyaa049 |
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