FeatureExtraction is part of HADES.
An R package for generating features (covariates) for a cohort using data in the Common Data Model.
- 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.
FeatureExtraction is an R package, with some functions implemented in C++.
Requires R (version 3.2.2 or higher). Installation on Windows requires RTools. FeatureExtraction require Java.
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See the instructions here for configuring your R environment, including RTools and Java.
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In R, use the following commands to download and install FeatureExtraction:
install.packages("drat")
drat::addRepo("OHDSI")
install.packages("FeatureExtraction")The documentation website can be found at https://ohdsi.github.io/FeatureExtraction/. PDF versions of the vignettes and package manual are here:
- Vignette: Using FeatureExtraction
- Vignette: Creating covariates using cohort attributes
- Vignette: Creating custom covariate builders
- Vignette: Creating covariates based on other cohorts
- Package manual: FeatureExtraction manual
These vignettes are also available in Korean:
- Vignette: Using FeatureExtraction
- Vignette: Creating custom covariate builders
- Developer questions/comments/feedback: OHDSI Forum
- We use the GitHub issue tracker for all bugs/issues/enhancements
Read here how you can contribute to this package.
FeatureExtraction is licensed under Apache License 2.0
FeatureExtraction is being developed in R Studio.
Ready for use
- This project is supported in part through the National Science Foundation grant IIS 1251151.