Automated data-adaptive analytics for electronic healthcare data to study causal treatment effects

BACKGROUND: Decision makers in health care increasingly rely on nonrandomized database analyses to assess the effectiveness, safety, and value of medical products. Health care data scientists use data-adaptive approaches that automatically optimize confounding control to study causal treatment effec...

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Detalles Bibliográficos
Autor principal: Schneeweiss, Sebastian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2018
Materias:
Review
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6039060/
https://www.ncbi.nlm.nih.gov/pubmed/30013400
http://dx.doi.org/10.2147/CLEP.S166545

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6039060/
https://www.ncbi.nlm.nih.gov/pubmed/30013400
http://dx.doi.org/10.2147/CLEP.S166545

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