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clinspacy  

Clinical Natural Language Processing using 'spaCy', 'scispaCy', and 'medspaCy'
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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]
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
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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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