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.
- 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.
DeepPatientLevelPrediction is an R package. It uses torch in R to build deep learning models without using python.
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.
- To install the package please read the Package installation guide
- Please read the main vignette for the package: Building Deep Learning Models
Documentation can be found on the package website.
PDF versions of the documentation are also available, as mentioned above.
- Developer questions/comments/feedback: OHDSI Forum
- We use the GitHub issue tracker for all bugs/issues/enhancements
Read here how you can contribute to this package.
DeepPatientLevelPrediction is licensed under Apache License 2.0
DeepPatientLevelPrediction is being developed in R Studio.