Impact of longitudinal data-completeness of electronic health record data on risk score misclassification is a research paper published in Journal of the American Medical Informatics Association (2022). On theSindex it has a DataRank of 0. It has been cited 12 times.
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NIH
Grant: R01LM012594
NIH
Grant: R01LM013204
National Institutes of Health
Grant: 1R01LM013204-01A1
Developing scalable algorithms to incorporate unstructured electronic health records for causal inference based on real-world data
National Institutes of Health
Grant: 1R01LM012594-01
Improving comparative effectiveness research through electronic health records continuity cohorts
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Sustainable Development Goals
Additional file 1 of Data quality considerations for evaluating COVID-19 treatments using real world data: learnings from the National COVID Cohort Collaborative (N3C)
Additional file 1 of Data quality considerations for evaluating COVID-19 treatments using real world data: learnings from the National COVID Cohort Collaborative (N3C)