https://github.com/OHDSI/FeatureExtraction
An R package for generating features (covariates) for a cohort using data in the Common Data Model.
https://github.com/OHDSI/FeatureExtraction
hades
Last synced: 4 months ago
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An R package for generating features (covariates) for a cohort using data in the Common Data Model.
- Host: GitHub
- URL: https://github.com/OHDSI/FeatureExtraction
- Owner: OHDSI
- Created: 2016-03-25T12:11:04.000Z (about 9 years ago)
- Default Branch: main
- Last Pushed: 2024-10-18T15:02:02.000Z (6 months ago)
- Last Synced: 2024-11-22T19:41:05.097Z (5 months ago)
- Topics: hades
- Language: R
- Homepage: http://ohdsi.github.io/FeatureExtraction/
- Size: 33 MB
- Stars: 61
- Watchers: 31
- Forks: 60
- Open Issues: 48
-
Metadata Files:
- Readme: README.md
- Changelog: NEWS.md
Awesome Lists containing this project
- jimsghstars - OHDSI/FeatureExtraction - An R package for generating features (covariates) for a cohort using data in the Common Data Model. (R)
README
FeatureExtraction
=================
[](https://github.com/OHDSI/FeatureExtraction/actions?query=workflow%3AR-CMD-check)
[](https://app.codecov.io/github/OHDSI/FeatureExtraction?branch=main)
[](https://CRAN.R-project.org/package=FeatureExtraction)
FeatureExtraction is part of [HADES](https://ohdsi.github.io/Hades/).
Introduction
============
An R package for generating features (covariates) for a cohort using data in the Common Data Model.
Features
========
- Takes a cohort as input.
- Generates baseline features for that cohort.
- Default covariates include all drugs, diagnoses, procedures, as well as age, comorbidity indexes, etc.
- Support for creating custom covariates.
- Generate paper-ready summary table of select population characteristics.
Technology
==========
FeatureExtraction is an R package, with some functions implemented in C++.
System Requirements
===================
Requires R (version 3.2.2 or higher). Installation on Windows requires [RTools](https://cran.r-project.org/bin/windows/Rtools/). FeatureExtraction require Java.
Getting Started
===============
1. See the instructions [here](https://ohdsi.github.io/Hades/rSetup.html) for configuring your R environment, including RTools and Java.
3. In R, use the following commands to download and install FeatureExtraction:
```r
install.packages("drat")
drat::addRepo("OHDSI")
install.packages("FeatureExtraction")
```
User Documentation
==================
The documentation website can be found at [https://ohdsi.github.io/FeatureExtraction/](https://ohdsi.github.io/FeatureExtraction/). PDF versions of the vignettes and package manual are here:
* Vignette: [Using FeatureExtraction](https://raw.githubusercontent.com/OHDSI/FeatureExtraction/main/inst/doc/UsingFeatureExtraction.pdf)
* Vignette: [Creating covariates using cohort attributes](https://raw.githubusercontent.com/OHDSI/FeatureExtraction/main/inst/doc/CreatingCovariatesUsingCohortAttributes.pdf)
* Vignette: [Creating custom covariate builders](https://raw.githubusercontent.com/OHDSI/FeatureExtraction/main/inst/doc/CreatingCustomCovariateBuilders.pdf)
* Vignette: [Creating covariates based on other cohorts](https://raw.githubusercontent.com/OHDSI/FeatureExtraction/main/inst/doc/CreatingCovariatesBasedOnOtherCohorts.pdf)
* Package manual: [FeatureExtraction manual](https://raw.githubusercontent.com/OHDSI/FeatureExtraction/main/extras/FeatureExtraction.pdf)
These vignettes are also available in Korean:
* Vignette: [Using FeatureExtraction](https://raw.githubusercontent.com/OHDSI/FeatureExtraction/main/inst/doc/UsingFeatureExtractionKorean.pdf)
* Vignette: [Creating custom covariate builders](https://raw.githubusercontent.com/OHDSI/FeatureExtraction/main/inst/doc/CreatingCustomCovariateBuildersKorean.pdf)
Support
=======
* Developer questions/comments/feedback: OHDSI Forum
* We use the GitHub issue tracker for all bugs/issues/enhancements
Contributing
============
Read [here](https://ohdsi.github.io/Hades/contribute.html) how you can contribute to this package.
License
=======
FeatureExtraction is licensed under Apache License 2.0
Development
===========
FeatureExtraction is being developed in R Studio.
### Development status
Ready for use
# Acknowledgements
- This project is supported in part through the National Science Foundation grant IIS 1251151.