Skip to content

AI-READI/ehr-omop

Repository files navigation

EHR-OMOP-pipeline

EHR datasets from AI-READi sites undergo cleaning, ingestion, and harmonization in the OMOP CDM data acquisition workstream, resulting in a unified LDS dataset for research. The overall data curation workflow and pipeline steps are documented and shared in ghis GitHub.

Contributors - Johns Hopkins University School of Medicine, Biomedical Informatics and Data Science, AI-READi data standards team : Stephanie Hong, Jessica Mitchell, Monique Banguidi, Yvette Chen, James Cavallon, Tricia Francis, Christpher Chute.

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published