PatientLevelPrediction
6.6.0Develop Clinical Prediction Models Using the Common Data Model
Overview
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.
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- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0812 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-05-2413 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-05-1712 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-05-1513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Show 4 earlier snapshots
- ERROR2026-05-1312 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-04-0614 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-0413 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 85%
- Documented parameters
- 95%
- Return-value docs
- 98%
- References docs
- 0%
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Checks run against github.com/ohdsi/patientlevelprediction on 2026-07-19.
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Code & Tests
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Package metadata
- First published
- 2025-02-11
- Total releases
- 5 / 1 yrs
- License
- Apache License 2.0 OSI
- Minimum R
- ≥ 4.0.0
- Bundled data
- 3.8 KB / 1 file
- Download size
- 3.0 MB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet