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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>.
| Version: | 0.1.0 |
| Suggests: | knitr, rmarkdown, testthat |
| Published: | 2021-01-07 |
| DOI: | 10.32614/CRAN.package.PheNorm |
| Author: | Sheng Yu [aut], Victor Castro [aut], Clara-Lea Bonzel [aut, cre], Molei Liu [aut], Chuan Hong [aut], Tianxi Cai [aut], PARSE LTD [aut] |
| Maintainer: | Clara-Lea Bonzel <clbonzel at hsph.harvard.edu> |
| BugReports: | https://github.com/celehs/PheNorm/issues |
| License: | GPL-3 |
| URL: | https://github.com/celehs/PheNorm |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | PheNorm results |
| Reference manual: | PheNorm.pdf |
| Vignettes: |
my-vignette |
| Package source: | PheNorm_0.1.0.tar.gz |
| Windows binaries: | r-devel: PheNorm_0.1.0.zip, r-release: PheNorm_0.1.0.zip, r-oldrel: PheNorm_0.1.0.zip |
| macOS binaries: | r-release (arm64): PheNorm_0.1.0.tgz, r-oldrel (arm64): PheNorm_0.1.0.tgz, r-release (x86_64): PheNorm_0.1.0.tgz, r-oldrel (x86_64): PheNorm_0.1.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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