Information Bottleneck for Estimating Treatment Effects with Systematically Missing Covariates

Estimating the effects of an intervention from high-dimensional observational data is a challenging problem due to the existence of confounding. The task is often further complicated in healthcare applications where a set of observations may be entirely missing for certain patients at test time, the...

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Detalles Bibliográficos
Autores principales: Parbhoo, Sonali, Wieser, Mario, Wieczorek, Aleksander, Roth, Volker
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516862/
https://www.ncbi.nlm.nih.gov/pubmed/33286163
http://dx.doi.org/10.3390/e22040389

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516862/
https://www.ncbi.nlm.nih.gov/pubmed/33286163
http://dx.doi.org/10.3390/e22040389

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