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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...
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 |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
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 |
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