DESCRIPTION

Package: PatientLevelPrediction
Type: Package
Title: Developing patient level prediction using data in the OMOP Common Data
    Model
Version: 6.3.9
Date: 2024-08-21
Authors@R: c(
    person("Jenna", "Reps", email = "jreps@its.jnj.com", role = c("aut", "cre")),
    person("Martijn", "Schuemie", role = c("aut")),
    person("Marc", "Suchard", role = c("aut")),
    person("Patrick", "Ryan", role = c("aut")),
    person("Peter", "Rijnbeek", role = c("aut")),
    person("Egill", "Fridgeirsson", role = c("aut"))
    )
Maintainer: Jenna Reps <jreps@its.jnj.com>
Description: A user friendly way to create patient level prediction models using the OMOP common data model. Given a
    cohort of interest and an outcome of interest, the package can use data in the
    OMOP Common Data Model to build a large set of features. These features can then
    be assessed to fit a predictive model using a number of machine learning algorithms.
    Several performance measures are implemented for model evaluation.
License: Apache License 2.0
URL: https://ohdsi.github.io/PatientLevelPrediction, https://github.com/OHDSI/PatientLevelPrediction
BugReports: https://github.com/OHDSI/PatientLevelPrediction/issues
VignetteBuilder: knitr
Depends:
    R (>= 4.0.0)
Imports:
    Andromeda,
    Cyclops (>= 3.0.0),
    DatabaseConnector (>= 6.0.0),
    dplyr,
    FeatureExtraction (>= 3.0.0),
    ggplot2,
    gridExtra,
    Matrix,
    memuse,
    mgcv,
    ParallelLogger (>= 2.0.0),
    polspline,
    pROC,
    PRROC,
    reticulate (>= 1.30),
    rlang,
    SqlRender (>= 1.1.3),
    survival,
    tidyr,
    utils
Suggests:
    AUC,
    BigKnn (>= 1.0.0),
    devtools,
    Eunomia,
    IterativeHardThresholding,
    knitr,
    markdown,
    Metrics,
    parallel,
    plyr, 
    pool,
    readr,
    ResourceSelection,
    ResultModelManager (>= 0.2.0),
    rmarkdown,
    RSQLite,
    scoring,
    ShinyAppBuilder (>= 1.1.1),
    survminer,
    testthat,
    withr,
    xgboost (> 1.3.2.1),
    lightgbm
Remotes:
    ohdsi/BigKnn,
    ohdsi/FeatureExtraction,
    ohdsi/ShinyAppBuilder,
    ohdsi/ResultModelManager,
RoxygenNote: 7.3.1
Encoding: UTF-8