Unsupervised Gold-Standard Label Free Phenotyping Algorithm for EHR Data
Overview
The algorithm combines the most predictive variable, such as count of the main International Classification of Diseases (ICD) codes, and other Electronic Health Record (EHR) features (e.g. health utilization and processed clinical note data), to obtain a score for accurate risk prediction and disease classification. In particular, it normalizes the surrogate to resemble gaussian mixture and leverages the remaining features through random corruption denoising. Background and details about the method can be found at Yu et al. (2018) doi:10.1093/jamia/ocx111.
Install
Health
- OK13 OK2026-09-08
- ERROR12 OK, 1 ERROR2026-09-07
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 1
- Examples that run
- 0%1 never run
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
- my-vignette HTML
Downloads
Repository
Issues over time
5 development-tooling and community-health practices detected across 3 families in the upstream repository
Checks run against github.com/celehs/phenorm on 2026-10-22.
GitHub Pages site last deployed 2021-02-23
Dependencies
Installing PheNorm adds no packages beyond those that come with R.
Code & Tests
People & History
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 0.1.0Latest2021-01-07 · current release
- RR 4.0.0 released · 2020-04-24
Package metadata
- First published
- 2021-01-07
- Total releases
- 1 / 5 yrs
- License
- GPL-3 OSI
- Download size
- 8.9 KB
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