Estimating summary statistics for electronic health record laboratory data for use in high-throughput phenotyping algorithms

We study the question of how to represent or summarize raw laboratory data taken from an electronic health record (EHR) using parametric model selection to reduce or cope with biases induced through clinical care. It has been previously demonstrated that the health care process (Hripcsak and Albers,...

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Detalles Bibliográficos
Autores principales: Albers, D.J., Elhadad, N., Claassen, J., Perotte, R., Goldstein, A., Hripcsak, G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5856130/
https://www.ncbi.nlm.nih.gov/pubmed/29369797
http://dx.doi.org/10.1016/j.jbi.2018.01.004

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5856130/
https://www.ncbi.nlm.nih.gov/pubmed/29369797
http://dx.doi.org/10.1016/j.jbi.2018.01.004

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