Variational Bayes for Latent Patient Phenotypes in EHR
Overview
Identification of Latent Patient Phenotype from Electronic Health Records (EHR) Data using Variational Bayes Gaussian Mixture Model for Latent Class Analysis and Variational Bayes regression for Biomarker level shifts, both implemented by Coordinate Ascent Variational Inference algorithms. Variational methods are used to enable Bayesian analysis of very large Electronic Health Records data. For VB GMM details see Bishop (2006,ISBN:9780-387-31073-2). For Logistic VB see Jaakkola and Jordan (2000) doi:10.1023/A:1008932416310. Please see preprint of JSS-submitted paper doi:10.48550/arXiv.2512.14272.
- Vignette changed to preprint paper on arxiv (https://doi.org/10.48550/arXiv.2512.14272) and submitted to Journal of Statistical Software.
From NEWS.md in the release
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- 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
- 9 (1 internal)includes a package overview page
- Examples that run
- 0%3 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
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- Help pages citing references
- 11%
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Repository
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GitHub Pages site last deployed 2025-12-17
Dependencies
Installing VBphenoR adds 28 packages (13 with compiled code, 26 MB of source tarballs). Heaviest: ggplot2 6.0 MB, data.table 5.7 MB, dbscan 3.8 MB.
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Package metadata
- First published
- 2025-09-15
- Total releases
- 2 / 1 yrs
- License
- MIT + file LICENCE OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 971 KB / 1 file
- Download size
- 1.0 MB
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