Imputation of missing values for electronic health record laboratory data

Imputation of missing values for electronic health record laboratory data

Abstract 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...

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Bibliographic Details
Main Authors: Jiang Li, Xiaowei S. Yan, Durgesh Chaudhary, Venkatesh Avula, Satish Mudiganti, Hannah Husby, Shima Shahjouei, Ardavan Afshar, Walter F. Stewart, Mohammed Yeasin, Ramin Zand, Vida Abedi
Format: Article
Language:English
Published: Nature Portfolio 2021-10-01
Series:npj Digital Medicine
Online Access:https://doi.org/10.1038/s41746-021-00518-0

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https://doi.org/10.1038/s41746-021-00518-0

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