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年10月15日
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>
NeedsCompilation:
no
Documentation:
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:
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