Pipeline to Detect Clinical Concepts (WIP Modifier)

Description

This pretrained pipeline is built on the top of jsl_ner_wip_modifier_clinical model.

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How to use

pipeline = PretrainedPipeline("jsl_ner_wip_modifier_clinical_pipeline", "en", "clinical/models")

pipeline.annotate("EXAMPLE MEDICAL TEXT")
val pipeline = new PretrainedPipeline("jsl_ner_wip_modifier_clinical_pipeline", "en", "clinical/models")

pipeline.annotate("EXAMPLE MEDICAL TEXT")
import nlu
nlu.load("en.med_ner.wip_modifier_clinical.pipeline").predict("""EXAMPLE MEDICAL TEXT""")

Model Information

Model Name: jsl_ner_wip_modifier_clinical_pipeline
Type: pipeline
Compatibility: Healthcare NLP 3.4.1+
License: Licensed
Edition: Official
Language: en
Size: 1.7 GB

Included Models

  • DocumentAssembler
  • SentenceDetectorDLModel
  • TokenizerModel
  • WordEmbeddingsModel
  • MedicalNerModel
  • NerConverter