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An R package for performing patient level prediction using deep learning in an observational database in the OMOP Common Data Model.

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OHDSI/DeepPatientLevelPrediction

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DeepPatientLevelPrediction

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Introduction

DeepPatientLevelPrediction is an R package for building and validating deep learning patient-level predictive models using data in the OMOP Common Data Model format and OHDSI PatientLevelPrediction framework.

Reps JM, Schuemie MJ, Suchard MA, Ryan PB, Rijnbeek PR. Design and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data. J Am Med Inform Assoc. 2018;25(8):969-975.

Features

  • Adds deep learning models to use in the OHDSI PatientLevelPrediction framework.
  • Allows to add custom deep learning models.
  • Includes an MLP, ResNet and a Transformer
  • Allows to use all the features of PatientLevelPrediction to validate and explore your model performance.

Technology

DeepPatientLevelPrediction is an R package. It uses torch in R to build deep learning models without using python.

System Requirements

Requires R (version 4.0.0 or higher). Installation on Windows requires RTools. For training deep learning models in most cases an nvidia GPU is required using either Windows or Linux.

Getting Started

User Documentation

Documentation can be found on the package website.

PDF versions of the documentation are also available, as mentioned above.

Support

Contributing

Read here how you can contribute to this package.

License

DeepPatientLevelPrediction is licensed under Apache License 2.0

Development

DeepPatientLevelPrediction is being developed in R Studio.

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An R package for performing patient level prediction using deep learning in an observational database in the OMOP Common Data Model.

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