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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:	6.5.1
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,pkgload,polspline,readr,ResourceSelection,ResultModelManager (≥ 0.6.0),reticulate (≥ 1.41),rmarkdown,RSQLite,scoring,survival,survminer,testthat,withr,xgboost (> 1.3.2.1)
Published:	2025-10-15
DOI:	10.32614/CRAN.package.PatientLevelPrediction
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.html ,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_6.5.1.tar.gz
Windows binaries:	r-devel:PatientLevelPrediction_6.5.1.zip, r-release:PatientLevelPrediction_6.5.1.zip, r-oldrel:PatientLevelPrediction_6.5.1.zip
macOS binaries:	r-release (arm64):PatientLevelPrediction_6.5.1.tgz, r-oldrel (arm64):PatientLevelPrediction_6.5.1.tgz, r-release (x86_64):PatientLevelPrediction_6.5.1.tgz, r-oldrel (x86_64):PatientLevelPrediction_6.5.1.tgz
Old sources:	PatientLevelPrediction archive

Linking:

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