Explain Clinical Doc ERA

Description

A pretrained pipeline with ner_clinical_events, assertion_dl and re_temporal_events_clinical. It will extract clinical entities, assign assertion status and find temporal relationships between clinical entities

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How to use


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

annotations = pipeline.annotate(text)

annotations.keys()


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

annotations = pipeline.annotate(text)

annotations.keys()

Results

THe output is a dictionary with the following keys: ‘sentences’, ‘clinical_ner_tags’, ‘clinical_ner_chunks_re’, ‘document’, ‘clinical_ner_chunks’, ‘assertion’, ‘clinical_relations’, ‘tokens’, ‘embeddings’, ‘pos_tags’, ‘dependencies’.

Model Information

Model Name: explain_clinical_doc_era_en_2.5.5_2.4
Type: pipeline
Compatibility: Spark NLP 2.5.5
License: Licensed
Edition: Official
Language: [en]

Included Models

  • ner_clinical_events
  • assertion_dl
  • re_temporal_events_clinical