diff --git a/website/meta/universe.json b/website/meta/universe.json index cd8f25890..eb4508498 100644 --- a/website/meta/universe.json +++ b/website/meta/universe.json @@ -3882,6 +3882,48 @@ "twitter": "_knrd" }, "category": ["scientific", "standalone"] + }, + { + "id": "edsnlp", + "title": "EDS-NLP", + "slogan": "spaCy components to extract information from clinical notes written in French.", + "description": "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](https://aphp.github.io/edsnlp/demo/)!", + "github": "aphp/edsnlp", + "pip": "edsnlp", + "code_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" + ], + "code_language": "python", + "url": "https://aphp.github.io/edsnlp/", + "author": "AP-HP", + "author_links": { + "github": "aphp", + "website": "https://github.com/aphp" + }, + "category": ["biomedical", "scientific", "research", "pipeline"], + "tags": ["clinical"] } ],