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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>.

Versions across snapshots

VersionRepositoryFileSize
6.6.0 rolling linux/jammy R-4.5 PatientLevelPrediction_6.6.0.tar.gz 2.2 MiB
6.6.0 rolling linux/noble R-4.5 PatientLevelPrediction_6.6.0.tar.gz 2.2 MiB
6.6.0 rolling source/ R- PatientLevelPrediction_6.6.0.tar.gz 3.0 MiB
6.6.0 latest linux/jammy R-4.5 PatientLevelPrediction_6.6.0.tar.gz 2.2 MiB
6.6.0 latest linux/noble R-4.5 PatientLevelPrediction_6.6.0.tar.gz 2.2 MiB
6.6.0 latest source/ R- PatientLevelPrediction_6.6.0.tar.gz 3.0 MiB
6.6.0 2026-04-26 source/ R- PatientLevelPrediction_6.6.0.tar.gz 3.0 MiB
6.6.0 2026-04-23 source/ R- PatientLevelPrediction_6.6.0.tar.gz 3.0 MiB
6.6.0 2026-04-09 windows/windows R-4.5 PatientLevelPrediction_6.6.0.zip 2.2 MiB
6.4.0 2025-04-20 source/ R- PatientLevelPrediction_6.4.0.tar.gz 2.9 MiB

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