medspacy: Performs biomedical named entity recognition, Unified Medical...
In ML4LHS/medspacy: Medical Natural Language Processing using spaCy, scispacy, and negspacy
Description
Usage
Arguments
Value
Examples
Description
Performs biomedical named entity recognition, Unified Medical Language System (UMLS)
concept mapping, and negation detection using the Python spaCy, scispacy, and negspacy packages.
Usage
1
Arguments
text
A character string containing medical text that you would like to process.
Value
A data frame containing the UMLS concept unique identifiers (cui), entities,
lemmatized entities, and NegEx negation status (TRUE means negated, FALSE means *not* negated).
Examples
1
medspacy('This patient has diabetes and CKD stage 3 but no HTN.')
ML4LHS/medspacy documentation built on Aug. 13, 2020, 12:26 a.m.
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Description Usage Arguments Value Examples
Description
Performs biomedical named entity recognition, Unified Medical Language System (UMLS) concept mapping, and negation detection using the Python spaCy, scispacy, and negspacy packages.
Usage
1 |
Arguments
text |
A character string containing medical text that you would like to process. |
Value
A data frame containing the UMLS concept unique identifiers (cui), entities,
lemmatized entities, and NegEx negation status (TRUE means negated, FALSE means *not* negated).
Examples
1 | medspacy('This patient has diabetes and CKD stage 3 but no HTN.')
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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