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Generating high-fidelity privacy-conscious synthetic patient data for causal effect estimation with multiple treatments
In the past decade, there has been exponentially growing interest in the use of observational data collected as a part of routine healthcare practice to determine the effect of a treatment with causal inference models. Validation of these models, however, has been a challenge because the ground trut...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9515575/ https://www.ncbi.nlm.nih.gov/pubmed/36187323 http://dx.doi.org/10.3389/frai.2022.918813 |