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clinspacy
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Download and install clinspacy package within the R console
Install from CRAN:
install.packages("clinspacy")
Install from Github:
library("remotes")
install_github("cran/clinspacy") Install by package version:
library("remotes")
install_version("clinspacy", "1.0.2") Attach the package and use:
library("clinspacy")
Maintained by
Karandeep Singh
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-03-20
Latest Update: 2021-03-20
Description:
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) . The 'medspacy' package uses
'ConText', an algorithm for determining the context of clinical statements
described by Harkema (2009) . Clinspacy
also supports entity embeddings from 'scispaCy' and UMLS 'cui2vec' concept
embeddings developed by Beam (2018) .
How to cite:
Karandeep Singh (2021). clinspacy: Clinical Natural Language Processing using 'spaCy', 'scispaCy', and 'medspaCy'. R package version 1.0.2, https://cran.r-project.org/web/packages/clinspacy. Accessed 28 Aug. 2026.
Previous versions and publish date:
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Complete documentation for clinspacy
Functions, R codes and Examples using
the clinspacy R package
Some associated functions: bind_clinspacy . bind_clinspacy_embeddings . clinspacy . clinspacy_init . dataset_cui2vec_definitions . dataset_cui2vec_embeddings . dataset_mtsamples . pipe .
Some associated R codes: clinspacy.R . cui2vec_data.R . mtsamples.R . utils-data-table.R . utils-pipe.R . Full clinspacy package functions and examples
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