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Agreement rate data set for GENETEX manuscript

<p><strong>Objectives:</strong> Clinico-Genomic Data (CGD) acquired through routine clinical practice has the potential to improve our understanding of clinical oncology. However, these data often reside in heterogeneous and semi-structured data, resulting in prolonged time-to-analyses.<br> <strong>Materials and Methods:</strong> We created GENETEX: an R package and Shiny application for text mining genomic reports from EHR and direct import into REDCap<sup>®</sup>.<br> <strong>Results:</strong> GENETEX facilitates the abstraction of CGD from EHR and streamlines capture of structured data into REDCap<sup>®</sup>. Its functions include natural language processing of key genomic information, transformation of semi-structured data into structured data and importation into REDCap. When evaluated with manual abstraction, GENETEX had &gt;99% agreement and captured CGD in approximately one-fifth the time.<br> <strong>Conclusions:</strong> GENETEX is freely available under the Massachusetts Institute of Technology license and can be obtained from GitHub. GENETEX is executed in R and deployed as a Shiny application for non-R users. It produces high-fidelity abstraction of CGD in a fraction of the time.</p>

ShareScore

32/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
12
Access
12
Reuse readiness
0
Engagement
4

Topics