Getting started¶

Install¶

pip install cava_nlp

Create an NLP pipeline¶

from cava_nlp.language import CaVaLang
n = CaVaLang()
n.add_pipe("clinical_normalizer", first=True)
n.add_pipe("rule_engine", name="ecog_value", config={...})
doc = n("The patient's ECOG score is 2.")
for ent in doc.ents:
    print(ent.text, ent.label_, ent._.normalisation)