yorgosa / featureextraction

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

FeatureExtraction

FeatureExtraction is part of the OHDSI Methods Library.

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. On Windows, make sure RTools is installed.
2. FeatureExtraction as well as the DatabaseConnector and SqlRender packages require Java. Java can be downloaded from http://www.java.com.
3. 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 http://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
• Package manual: FeatureExtraction manual

Support

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

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.