clinspacy: Clinical Natural Language Processing using 'spaCy', 'scispaCy', and 'medspaCy'

Performs biomedical named entity recognition, Unified Medical Language System (UMLS) concept mapping, and negation detection using the Python 'spaCy', 'scispaCy', and 'medspaCy' packages, and transforms extracted data into a wide format for inclusion in machine learning models. The development of the 'scispaCy' package is described by Neumann (2019) <doi:10.18653/v1/W19-5034>. The 'medspacy' package uses 'ConText', an algorithm for determining the context of clinical statements described by Harkema (2009) <doi:10.1016/j.jbi.2009.05.002>. Clinspacy also supports entity embeddings from 'scispaCy' and UMLS 'cui2vec' concept embeddings developed by Beam (2018) <arXiv:1804.01486>.

Version: 1.0.2
Depends: R (≥ 2.10)
Imports: reticulate (≥ 1.16), data.table, assertthat, rappdirs, utils, magrittr
Suggests: knitr, rmarkdown
Published: 2021-03-20
Author: Karandeep Singh [aut, cre], Benjamin Kompa [aut], Andrew Beam [aut], Allen Schmaltz [aut]
Maintainer: Karandeep Singh <kdpsingh at>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README NEWS
CRAN checks: clinspacy results


Reference manual: clinspacy.pdf
Package source: clinspacy_1.0.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: clinspacy_1.0.2.tgz, r-oldrel: clinspacy_1.0.2.tgz


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