A shiny app to visualize the knowledge networks for the code concepts. Using co-occurrence matrices of EHR codes from Veterans Affairs (VA) and Massachusetts General Brigham (MGB), the knowledge extraction via sparse embedding regression (KESER) algorithm was used to construct knowledge networks for the code concepts. Background and details about the method can be found at Chuan et al. (2021) <doi:10.1038/s41746-021-00519-z>.
Version: |
0.1.0 |
Depends: |
R (≥ 3.5.0), shinyBS, shiny, htmltools |
Imports: |
config (≥ 0.3.1), data.table, dplyr, DT, ggplot2, golem (≥
0.3.1), plotly, reactable, rintrojs, rlang, shinycssloaders, shinydashboard, shinydashboardPlus, shinyhelper, shinyWidgets, stringr, visNetwork, yaml |
Suggests: |
rmarkdown, knitr, shinytest, testthat (≥ 3.0.0) |
Published: |
2022-03-03 |
DOI: |
10.32614/CRAN.package.kesernetwork |
Author: |
Su-Chun Cheng [cre, aut],
PARSE LTD [aut],
VA CIPHER [aut],
Verity Research [aut],
CELEHS [aut] |
Maintainer: |
Su-Chun Cheng <scheng at parse-health.org> |
BugReports: |
https://github.com/celehs/kesernetwork/issues |
License: |
GPL (≥ 3) |
URL: |
https://github.com/celehs/kesernetwork |
NeedsCompilation: |
no |
Materials: |
README NEWS |
CRAN checks: |
kesernetwork results |