OHDSI/FeatureExtraction

Name: FeatureExtraction

Owner: Observational Health Data Sciences and Informatics

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

Created: 2016-03-25 12:11:04.0

Updated: 2017-12-30 07:07:19.0

Pushed: 2017-12-14 12:28:44.0

Homepage:

Size: 3978

Language: R

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README

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:

   all.packages("devtools")
   ary(devtools)
   all_github("ohdsi/SqlRender") 
   all_github("ohdsi/DatabaseConnector") 
   all_github("ohdsi/FeatureExtraction") 
   

Getting Involved

• 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

License

FeatureExtraction is licensed under Apache License 2.0

Development

FeatureExtraction is being developed in R Studio.

Development status

Beta

Acknowledgements

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