Universe

EDS-NLP

spaCy components to extract information from clinical notes written in French.

EDS-NLP provides a set of rule-based spaCy components to extract information for French clinical notes. It also features qualifier pipelines that detect negations, speculations and family context, among other modalities. Check out the demo!

Example

import spacy nlp = spacy.blank("fr") terms = dict( covid=["covid", "coronavirus"], ) # Sentencizer component, needed for negation detection nlp.add_pipe("eds.sentences") # Matcher component nlp.add_pipe("eds.matcher", config=dict(terms=terms)) # Negation detection nlp.add_pipe("eds.negation") # Process your text in one call ! doc = nlp("Le patient est atteint de covid") doc.ents # Out: (covid,) doc.ents[0]._.negation # Out: False
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Author info

AP-HP

GitHubaphp/edsnlp

Categories biomedical scientific research pipeline

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Read the docsJSON source