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kesernetwork

https://github.com/celehs/kesernetwork

Science Score: 36.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ○
    .zenodo.json file
  • ✓
    DOI references
    Found 2 DOI reference(s) in README
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    1 of 3 committers (33.3%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (14.1%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Basic Info
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 0
  • Open Issues: 1
  • Releases: 2
Created almost 5 years ago · Last pushed over 1 year ago
Metadata Files
Readme Changelog License Code of conduct

README.Rmd 

---
output: github_document
---



```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```


# kesernetwork


[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)


## Overview

The kesernetwork builds 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.

## Installation

Install the released version of kesernetwork from CRAN:

``` r
install.packages("kesernetwork")
```

Or install the development version from GitHub with:

``` r
install.packages("remotes")
remotes::install_github("celehs/kesernetwork")
```



## Usage

This is a basic example which shows you how to run the `kesernetwork` app. Remember you need to get access to the data and save it to your local computer. In order to guarantee some dependencies are loaded, you must use `library(kesernetwork)` beforehand, instead of directly running `kesernetwork::run_app()`.


```{r eval=FALSE}
library(kesernetwork)
run_app(Rdata_path = "path/to/kesernetwork.RData")
```



See the [getting started guide](https://celehs.github.io/kesernetwork/articles/main.html)
to learn how to use kesernetwork.



## Citations

- Hong, C., Rush, E., Liu, M. et al. Clinical knowledge extraction via sparse embedding regression (KESER) with multi-center large scale electronic health record data. npj Digit. Med. 4, 151 (2021). https://doi.org/10.1038/s41746-021-00519-z

Owner

  • Name: CELEHS
  • Login: celehs
  • Kind: user
  • Location: Boston, USA

Translational Data Science Center for a Learning Health System

GitHub Events

Total
  • Release event: 4
  • Delete event: 5
  • Push event: 8
  • Create event: 5
Last Year
  • Release event: 4
  • Delete event: 5
  • Push event: 8
  • Create event: 5

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 40
  • Total Committers: 3
  • Avg Commits per committer: 13.333
  • Development Distribution Score (DDS): 0.375
Past Year
  • Commits: 15
  • Committers: 2
  • Avg Commits per committer: 7.5
  • Development Distribution Score (DDS): 0.067
Top Committers
Name Email Commits
chenh2017 4****5@q****m 25
xiongxin0238 x****g@h****u 14
CELEHS 4****s 1
Committer Domains (Top 20 + Academic)
hsph.harvard.edu: 1 qq.com: 1

Issues and Pull Requests

Last synced: 12 months ago

All Time
  • Total issues: 0
  • Total pull requests: 15
  • Average time to close issues: N/A
  • Average time to close pull requests: less than a minute
  • Total issue authors: 0
  • Total pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 14
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
Pull Request Authors
  • xinxiong0238 (15)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • cran 175 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 1
  • Total maintainers: 1
cran.r-project.org: kesernetwork

Visualization of the KESER Network

  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 175 Last month
Rankings
Forks count: 28.8%
Dependent packages count: 29.8%
Stargazers count: 31.7%
Dependent repos count: 35.5%
Average: 37.1%
Downloads: 60.0%
Maintainers (1)
scheng@parse-health.org
Last synced: 10 months ago

Dependencies

DESCRIPTION cran
  • R >= 3.5.0 depends
  • htmltools * depends
  • shiny * depends
  • shinyBS * depends
  • DT * imports
  • Matrix * imports
  • config >= 0.3.1 imports
  • data.table * imports
  • dplyr * imports
  • ggplot2 * imports
  • golem >= 0.3.1 imports
  • plotly * imports
  • reactable * imports
  • rintrojs * imports
  • rlang * imports
  • shinyWidgets * imports
  • shinycssloaders * imports
  • shinydashboard * imports
  • shinydashboardPlus * imports
  • shinyhelper * imports
  • stringr * imports
  • visNetwork * imports
  • yaml * imports
  • knitr * suggests
  • rmarkdown * suggests
  • shinytest * suggests
  • testthat >= 3.0.0 suggests