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

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mi-erasmusmc/FeatureExtraction

 
 

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FeatureExtraction

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

Screenshots

Todo

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. Libraries used in FeatureExtraction require Java.

Dependencies

  • DatabaseConnector
  • SqlRender

Getting Started

  1. On Windows, make sure RTools is installed.
  2. 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("devtools")
library(devtools)
install_github("ohdsi/SqlRender") 
install_github("ohdsi/DatabaseConnector") 
install_github("ohdsi/FeatureExtraction") 

Getting Involved

License

FeatureExtraction is licensed under Apache License 2.0

Development

FeatureExtraction is being developed in R Studio.

Development status

Build Status

Beta

Acknowledgements

  • This project is supported in part through the National Science Foundation grant IIS 1251151.

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

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  • R 84.6%
  • Java 12.7%
  • C++ 2.5%
  • Shell 0.2%