Explain Clinical Doc CARP


A pretrained pipeline with ner_clinical, assertion_dl, re_clinical and ner_posology. It will extract clinical and medication entities, assign assertion status and find relationships between clinical entities.

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How to use

pipeline = PretrainedPipeline('explain_clinical_doc_carp', 'en', 'clinical/models')

annotations = pipeline.annotate("This is an example")


{'sentences': ['This is an example'],
 'clinical_ner_tags': ['O', 'O', 'O', 'O'],
 'document': ['This is an example'],
 'ner_chunks': [],
 'clinical_ner_chunks': [],
 'ner_tags': ['O', 'O', 'O', 'O'],
 'assertion': [],
 'clinical_relations': [],
 'tokens': ['This', 'is', 'an', 'example'],
 'embeddings': ['This', 'is', 'an', 'example'],
 'pos_tags': ['PND', 'VBZ', 'DD', 'NN'],
 'dependencies': ['example', 'example', 'example', 'ROOT']}

Model Information

Model Name: explain_clinical_doc_carp
Type: pipeline
Compatibility: Spark NLP 2.5.5
License: Licensed
Edition: Official
Language: [en]

Included Models

  • ner_clinical
  • assertion_dl
  • re_clinical
  • ner_posology