Implement surrogate-assisted feature extraction (SAFE) and common machine learning approaches to train and validate phenotyping models. Background and details about the methods can be found at Zhang et al. (2019) <doi:10.1038/s41596-019-0227-6>, Yu et al. (2017) <doi:10.1093/jamia/ocw135>, and Liao et al. (2015) <doi:10.1136/bmj.h1885>.
Version: | 1.2.1 |
Depends: | R (≥ 3.3.0) |
Imports: | graphics, methods, stats, utils, glmnet, RMySQL |
Suggests: | ggplot2, e1071, randomForestSRC, xgboost, knitr, rmarkdown |
Published: | 2020-09-17 |
Author: | Yichi Zhang [aut], Chuan Hong [aut], Tianxi Cai [aut], PARSE LTD [aut, cre] |
Maintainer: | PARSE LTD <software at parse-health.org> |
BugReports: | https://github.com/celehs/PheCAP/issues |
License: | GPL-3 |
URL: | https://celehs.github.io/PheCAP/, https://github.com/celehs/PheCAP |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | PheCAP results |
Reference manual: | PheCAP.pdf |
Vignettes: |
NER using MetaMAP Running NLP using NILE Example 1: Simulated Data Example 2: Real EHR Data Main Steps |
Package source: | PheCAP_1.2.1.tar.gz |
Windows binaries: | r-devel: PheCAP_1.2.1.zip, r-release: PheCAP_1.2.1.zip, r-oldrel: PheCAP_1.2.1.zip |
macOS binaries: | r-release (arm64): PheCAP_1.2.1.tgz, r-oldrel (arm64): PheCAP_1.2.1.tgz, r-release (x86_64): PheCAP_1.2.1.tgz, r-oldrel (x86_64): PheCAP_1.2.1.tgz |
Old sources: | PheCAP archive |
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