Imputation of missing values for electronic health record laboratory data

Laboratory data from Electronic Health Records (EHR) are often used in prediction models where estimation bias and model performance from missingness can be mitigated using imputation methods. We demonstrate the utility of imputation in two real-world EHR-derived cohorts of ischemic stroke from Geis...

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Detalles Bibliográficos
Autores principales: Li, Jiang, Yan, Xiaowei S., Chaudhary, Durgesh, Avula, Venkatesh, Mudiganti, Satish, Husby, Hannah, Shahjouei, Shima, Afshar, Ardavan, Stewart, Walter F., Yeasin, Mohammed, Zand, Ramin, Abedi, Vida
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8505441/
https://www.ncbi.nlm.nih.gov/pubmed/34635760
http://dx.doi.org/10.1038/s41746-021-00518-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8505441/
https://www.ncbi.nlm.nih.gov/pubmed/34635760
http://dx.doi.org/10.1038/s41746-021-00518-0

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