Package: FeatureExtraction 3.8.0
Ger Inberg
FeatureExtraction: Generating Features for a Cohort
An R interface for generating features for a cohort using data in the Common Data Model. Features can be constructed using default or custom made feature definitions. Furthermore it's possible to aggregate features and get the summary statistics.
Authors:
FeatureExtraction_3.8.0.tar.gz
FeatureExtraction_3.8.0.tar.gz(r-4.5-noble)FeatureExtraction_3.8.0.tar.gz(r-4.4-noble)
FeatureExtraction_3.8.0.tgz(r-4.4-emscripten)FeatureExtraction_3.8.0.tgz(r-4.3-emscripten)
FeatureExtraction.pdf |FeatureExtraction.html✨
FeatureExtraction/json (API)
NEWS
| # Install 'FeatureExtraction' in R: |
| install.packages('FeatureExtraction', repos = 'https://cloud.r-project.org') |
Bug tracker:https://github.com/ohdsi/featureextraction/issues52 issues
Last updated 14 days agofrom:c80764f887. Checks:1 OK, 2 WARNING. Indexed: no.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 19 2025 |
| R-4.5-linux | WARNING | Mar 19 2025 |
| R-4.4-linux | WARNING | Mar 19 2025 |
Exports:aggregateCovariatescomputeStandardizedDifferenceconvertPrespecSettingsToDetailedSettingscreateAnalysisDetailscreateCohortAttrCovariateSettingscreateCohortBasedCovariateSettingscreateCohortBasedTemporalCovariateSettingscreateCovariateSettingscreateDefaultCovariateSettingscreateDefaultTemporalCovariateSettingscreateDetailedCovariateSettingscreateDetailedTemporalCovariateSettingscreateEmptyCovariateDatacreateTable1createTable1CovariateSettingscreateTemporalCovariateSettingscreateTemporalSequenceCovariateSettingsfilterByCohortDefinitionIdfilterByRowIdgetDbCohortAttrCovariatesDatagetDbCohortBasedCovariatesDatagetDbCovariateDatagetDbDefaultCovariateDatagetDefaultTable1SpecificationsisAggregatedCovariateDataisCovariateDataisTemporalCovariateDataloadCovariateDatasaveCovariateDatashowsummarytidyCovariateData
Dependencies:Andromedabackportsbitbit64blobcachemcheckmateclicliprcpp11crayonDatabaseConnectorDBIdbplyrdigestdplyrfansifastmapgenericsgluehmsjsonlitelifecyclemagrittrmemoiseParallelLoggerpillarpkgconfigplogrprettyunitsprogresspurrrR6RcppreadrrJavarlangRSQLitesnowSqlRenderstringistringrtibbletidyrtidyselecttriebeardtzdburltoolsutf8vctrsvroomwithrxml2zip
Creating covariates based on other cohorts
Rendered fromCreatingCovariatesBasedOnOtherCohorts.Rmdusingknitr::rmarkdownon Mar 19 2025.Last update: 2024-05-02
Started: 2024-05-02
Creating covariates using cohort attributes
Rendered fromCreatingCovariatesUsingCohortAttributes.Rmdusingknitr::rmarkdownon Mar 19 2025.Last update: 2024-05-02
Started: 2024-05-02
Creating custom covariate builders
Rendered fromCreatingCustomCovariateBuilders.Rmdusingknitr::rmarkdownon Mar 19 2025.Last update: 2024-07-16
Started: 2024-05-02
Creating custom covariate builders (Korean)
Rendered fromCreatingCustomCovariateBuildersKorean.Rmdusingknitr::rmarkdownon Mar 19 2025.Last update: 2024-05-02
Started: 2024-05-02
Using FeatureExtraction
Rendered fromUsingFeatureExtraction.Rmdusingknitr::rmarkdownon Mar 19 2025.Last update: 2024-05-02
Started: 2024-05-02
Using FeatureExtraction (Korean)
Rendered fromUsingFeatureExtractionKorean.Rmdusingknitr::rmarkdownon Mar 19 2025.Last update: 2024-05-02
Started: 2024-05-02
Citation
To cite package ‘FeatureExtraction’ in publications use:
Schuemie M, Suchard M, Ryan P, Reps J, Sena A, Inberg G (2025). FeatureExtraction: Generating Features for a Cohort. R package version 3.8.0, https://CRAN.R-project.org/package=FeatureExtraction.
Corresponding BibTeX entry:
@Manual{,
title = {FeatureExtraction: Generating Features for a Cohort},
author = {Martijn Schuemie and Marc Suchard and Patrick Ryan and
Jenna Reps and Anthony Sena and Ger Inberg},
year = {2025},
note = {R package version 3.8.0},
url = {https://CRAN.R-project.org/package=FeatureExtraction},
}
Readme and manuals
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
-
See the instructions here for configuring your R environment, including RTools and Java.
-
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.