DESCRIPTION

Package: PatientLevelPrediction
Type: Package
Title: Package for patient level prediction using data in the OMOP Common Data
    Model
Version: 2.0.2
Date: 2018-04-24
Author: Jenna Reps [aut],
    Martijn J. Schuemie [aut, cre],
    Marc A. Suchard [aut],
    Patrick B. Ryan [aut],
    Peter R. Rijnbeek [aut]
Maintainer: Jenna Reps <reps@ohdsi.org>
Description: A package for creating patient level prediction models. 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
Depends:
    R (>= 3.3.0), 
    DatabaseConnector (>= 1.11.4),
    FeatureExtraction (>= 2.0.0),
    Cyclops (>= 1.2.2)
Imports:
    ggplot2,
    gridExtra,
    bit,
    ff,
    ffbase (>= 0.12.1),
    plyr,
    survAUC,
    Rcpp (>= 0.11.2),
    SqlRender (>= 1.1.3),
    survival,
    xgboost,
    Matrix,
    AUC,
    PythonInR,
    futile.options,
    futile.logger,
    utils,
    methods,
    BigKnn,
    reshape2,
    ReporteRs,
    diagram,
    shiny,
    plotly,
    DT,
    htmlwidgets (> 0.8),
    tidyr,
    viridisLite,
    RCurl,
    RJSONIO,
    keras,
    slam,
    magrittr
Suggests:
    testthat,
    pROC,
    gnm,
    knitr,
    rmarkdown,
    scoring,
    Metrics,
    SparseM,
    ResourceSelection
LinkingTo: Rcpp
NeedsCompilation: yes
RoxygenNote: 6.0.1