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A statistical learning method to simultaneously predict a range of target phenotypes using codified and natural language processing (NLP)-derived Electronic Health Record (EHR) data. See Ahuja et al (2020) JAMIA <doi:10.1093/jamia/ocaa079> for details.
| Version: | 0.1.0-1 |
| Depends: | R (≥ 3.0), Matrix |
| Imports: | pROC, glmnet, MAP, Rcpp, foreach, doParallel |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | knitr, rmarkdown |
| Published: | 2020-11-10 |
| DOI: | 10.32614/CRAN.package.sureLDA |
| Author: | Yuri Ahuja [aut, cre], Tianxi Cai [aut], PARSE LTD [aut] |
| Maintainer: | Yuri Ahuja <Yuri_Ahuja at hms.harvard.edu> |
| BugReports: | https://github.com/celehs/sureLDA/issues |
| License: | GPL-3 |
| URL: | https://github.com/celehs/sureLDA |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | sureLDA results |
| Reference manual: | sureLDA.pdf |
| Vignettes: |
Simulated Example |
| Package source: | sureLDA_0.1.0-1.tar.gz |
| Windows binaries: | r-devel: sureLDA_0.1.0-1.zip, r-release: sureLDA_0.1.0-1.zip, r-oldrel: sureLDA_0.1.0-1.zip |
| macOS binaries: | r-release (arm64): sureLDA_0.1.0-1.tgz, r-oldrel (arm64): sureLDA_0.1.0-1.tgz, r-release (x86_64): sureLDA_0.1.0-1.tgz, r-oldrel (x86_64): sureLDA_0.1.0-1.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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