Integration of genetic and clinical information to improve imputation of data missing from electronic health records.

ABSTRACT:

Objective

Clinical data of patients' measurements and treatment history stored in electronic health record (EHR) systems are starting to be mined for better treatment options and disease associations. A primary challenge associated with utilizing EHR data is the considerable amount of missing data. Failure to address this issue can introduce significant bias in EHR-based research. Currently, imputation methods rely on correlations among the structured phenotype variables in the EHR. However, genetic studies have shown that many EHR-based phenotypes have a heritable component, suggesting that measured genetic variants might be useful for imputing missing data. In this article, we developed a computational model that incorporates patients' genetic information to perform EHR data impu

SUBMITTER: Li R 

PROVIDER: S-EPMC6748821 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature