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 [aut], Samuel Zimmermann [aut], Johannes Vey [aut], Maximilian Pilz [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 resultsRetroSearch is an open source project built by @garambo | Open a GitHub Issue
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