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. Libraries used in FeatureExtraction require Java.
- On Windows, make sure RTools is installed.
- The DatabaseConnector and SqlRender packages require Java. Java can be downloaded from http://www.java.com.
- In R, use the following commands to download and install FeatureExtraction:
install.packages("devtools") library(devtools) install_github("ohdsi/SqlRender") install_github("ohdsi/DatabaseConnector") install_github("ohdsi/FeatureExtraction")
- Vignette: Using FeatureExtraction
- Vignette: Creating covariates using cohort attributes
- Vignette: Creating custom covariate builders
- Package manual: FeatureExtraction.pdf
- Developer questions/comments/feedback: OHDSI Forum
- We use the GitHub issue tracker for all bugs/issues/enhancements
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.