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.
|Author||Jenna Reps [aut], Martijn J. Schuemie [aut, cre], Marc A. Suchard [aut], Patrick B. Ryan [aut], Peter R. Rijnbeek [aut]|
|Maintainer||Jenna Reps <[email protected]>|
|License||Apache License 2.0|
|Package repository||View on GitHub|
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