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MetaNLP: Natural Language Processing for Meta Analysis

Given a CSV file with titles and abstracts, the package creates a document-term matrix that is lemmatized and stemmed and can directly be used to train machine learning methods for automatic title-abstract screening in the preparation of a meta analysis.

Version: 0.1.3
Depends: R (≥ 2.10)
Imports: glmnet, tm, textstem, methods, lexicon, utils
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0), covr, wordcloud, vdiffr
Published: 2024-11-07
DOI: 10.32614/CRAN.package.MetaNLP
Author: Nico Bruder ORCID iD [aut], Samuel Zimmermann ORCID iD [aut], Johannes Vey ORCID iD [aut], Maximilian Pilz ORCID iD [aut, cre], Institute of Medical Biometry - University of Heidelberg [cph]
Maintainer: Maximilian Pilz <maximilian.pilz at itwm.fraunhofer.de>
BugReports: https://github.com/imbi-heidelberg/MetaNLP/issues
License: MIT + file LICENSE
URL: https://github.com/imbi-heidelberg/MetaNLP
NeedsCompilation: no
Materials: README NEWS
In views: MetaAnalysis
CRAN checks: MetaNLP results

Documentation:

Reference manual: MetaNLP.pdf

Downloads:

Package source: MetaNLP_0.1.3.tar.gz
Windows binaries: r-devel: MetaNLP_0.1.3.zip, r-release: MetaNLP_0.1.3.zip, r-oldrel: MetaNLP_0.1.3.zip
macOS binaries: r-release (arm64): MetaNLP_0.1.3.tgz, r-oldrel (arm64): MetaNLP_0.1.3.tgz, r-release (x86_64): MetaNLP_0.1.3.tgz, r-oldrel (x86_64): MetaNLP_0.1.3.tgz
Old sources: MetaNLP archive

Linking:

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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.