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) <doi:10.48550/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 |
DOI: |
10.32614/CRAN.package.clinspacy |
Author: |
Karandeep Singh [aut, cre],
Benjamin Kompa [aut],
Andrew Beam [aut],
Allen Schmaltz [aut] |
Maintainer: |
Karandeep Singh <kdpsingh at umich.edu> |
BugReports: |
https://github.com/ML4LHS/clinspacy/issues |
License: |
MIT + file LICENSE |
URL: |
https://github.com/ML4LHS/clinspacy |
NeedsCompilation: |
no |
Materials: |
README NEWS |
CRAN checks: |
clinspacy results |
Documentation:
Downloads:
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