Building an OMOP common data model-compliant annotated corpus for COVID-19 clinical trials.

ABSTRACT: Clinical trials are essential for generating reliable medical evidence, but often suffer from expensive and delayed patient recruitment because the unstructured eligibility criteria description prevents automatic query generation for eligibility screening. In response to the COVID-19 pandemic, many trials have been created but their information is not computable. We included 700 COVID-19 trials available at the point of study and developed a semi-automatic approach to generate an annotated corpus for COVID-19 clinical trial eligibility criteria called COVIC. A hierarchical annotation schema based on the OMOP Common Data Model was developed to accommodate four levels of annotation granularity: i.e., study cohort, eligibility criteria, named entity and standard concept. In COVIC, 39 trials w

SUBMITTER: Sun Y 

PROVIDER: S-EPMC8079156 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature