Title: | Visualization of the KESER Network |
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Description: | 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>. |
Authors: | Su-Chun Cheng [cre, aut], PARSE LTD [aut], VA CIPHER [aut], Verity Research [aut], CELEHS [aut] |
Maintainer: | Su-Chun Cheng <[email protected]> |
License: | GPL (>= 3) |
Version: | 0.1.0 |
Built: | 2024-10-25 03:32:34 UTC |
Source: | https://github.com/celehs/kesernetwork |
Run the Shiny Application
run_app( Rdata_path = NULL, onStart = NULL, options = list(), enableBookmarking = "server", uiPattern = "/", ... )
run_app( Rdata_path = NULL, onStart = NULL, options = list(), enableBookmarking = "server", uiPattern = "/", ... )
Rdata_path |
path to Rdata files. |
onStart |
A function that will be called before the app is actually run.
This is only needed for |
options |
Named options that should be passed to the |
enableBookmarking |
Can be one of |
uiPattern |
A regular expression that will be applied to each |
... |
arguments to pass to golem_opts. See '?golem::get_golem_options' for more details. |
A shiny application.
if (interactive()) { run_app() }
if (interactive()) { run_app() }