PatientLevelPrediction: Develop Clinical Prediction Models Using the Common Data Model

A user friendly way to create patient level prediction models using the Observational Medical Outcomes Partnership Common Data Model. Given a cohort of interest and an outcome of interest, the package can use data in the Common Data Model to build a large set of features. These features can then be used to fit a predictive model with a number of machine learning algorithms. This is further described in Reps (2017) <doi:10.1093/jamia/ocy032>.

Version: 6.4.0
Depends: R (≥ 4.0.0)
Imports: Andromeda, Cyclops (≥ 3.0.0), DatabaseConnector (≥ 6.0.0), digest, dplyr, FeatureExtraction (≥ 3.0.0), Matrix, memuse, ParallelLogger (≥ 2.0.0), pROC, PRROC, rlang, SqlRender (≥ 1.1.3), tidyr, utils
Suggests: curl, Eunomia (≥ 2.0.0), glmnet, ggplot2, gridExtra, IterativeHardThresholding, knitr, lightgbm, Metrics, mgcv, OhdsiShinyAppBuilder (≥ 1.0.0), parallel, polspline, readr, ResourceSelection, ResultModelManager (≥ 0.2.0), reticulate (≥ 1.30), rmarkdown, RSQLite, scoring, survival, survminer, testthat, withr, xgboost (> 1.3.2.1)
Published: 2025-02-11
Author: Egill Fridgeirsson [aut, cre], Jenna Reps [aut], Martijn Schuemie [aut], Marc Suchard [aut], Patrick Ryan [aut], Peter Rijnbeek [aut], Observational Health Data Science and Informatics [cph]
Maintainer: Egill Fridgeirsson <e.fridgeirsson at erasmusmc.nl>
BugReports: https://github.com/OHDSI/PatientLevelPrediction/issues
License: Apache License 2.0
URL: https://ohdsi.github.io/PatientLevelPrediction/, https://github.com/OHDSI/PatientLevelPrediction
NeedsCompilation: no
Citation: PatientLevelPrediction citation info
Materials: README NEWS
CRAN checks: PatientLevelPrediction results

Documentation:

Reference manual: PatientLevelPrediction.pdf
Vignettes: Adding Custom Feature Engineering Functions (source, R code)
Adding Custom Patient-Level Prediction Algorithms (source, R code)
Adding Custom Sampling (source, R code)
Adding Custom Data Splitting (source, R code)
Benchmark Tasks (source)
Best Practices (source)
Automatically Build Multiple Patient-Level Predictive Models (source, R code)
Building patient-level predictive models (source, R code)
Clinical Models (source)
Constrained Predictors (source, R code)
Creating Learning Curves (source, R code)
Making patient-level predictive network study packages (source, R code)
Integration of GIS Data Into OHDSI Model Building (source, R code)
Patient-Level Prediction Installation Guide (source, R code)

Downloads:

Package source: PatientLevelPrediction_6.4.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): PatientLevelPrediction_6.4.0.tgz, r-oldrel (arm64): not available, r-release (x86_64): PatientLevelPrediction_6.4.0.tgz, r-oldrel (x86_64): not available

Linking:

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