ohdsi / featureextraction

An R package for generating features (covariates) for a cohort using data in the Common Data Model.

FeatureExtraction

FeatureExtraction is part of 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. FeatureExtraction require Java.

Getting Started

1. See the instructions here for configuring your R environment, including RTools and Java.

2. In R, use the following commands to download and install FeatureExtraction:

install.packages("drat")
drat::addRepo("OHDSI")
install.packages("FeatureExtraction")

User Documentation

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

Support

• Developer questions/comments/feedback: OHDSI Forum
• We use the GitHub issue tracker for all bugs/issues/enhancements

Contributing

Read here 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.