Pipeline to Extraction of Clinical Abbreviations and Acronyms

Description

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

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How to use

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


pipeline.annotate("Gravid with estimated fetal weight of 6-6/12 pounds. LOWER EXTREMITIES: No edema. LABORATORY DATA: Laboratory tests include a CBC which is normal. Blood Type: AB positive. Rubella: Immune. VDRL: Nonreactive. Hepatitis C surface antigen: Negative. HIV: Negative. One-Hour Glucose: 117. Group B strep has not been done as yet.")
val pipeline = new PretrainedPipeline("ner_abbreviation_clinical_pipeline", "en", "clinical/models")


pipeline.annotate("Gravid with estimated fetal weight of 6-6/12 pounds. LOWER EXTREMITIES: No edema. LABORATORY DATA: Laboratory tests include a CBC which is normal. Blood Type: AB positive. Rubella: Immune. VDRL: Nonreactive. Hepatitis C surface antigen: Negative. HIV: Negative. One-Hour Glucose: 117. Group B strep has not been done as yet.")
import nlu
nlu.load("en.med_ner.clinical-abbreviation.pipeline").predict("""Gravid with estimated fetal weight of 6-6/12 pounds. LOWER EXTREMITIES: No edema. LABORATORY DATA: Laboratory tests include a CBC which is normal. Blood Type: AB positive. Rubella: Immune. VDRL: Nonreactive. Hepatitis C surface antigen: Negative. HIV: Negative. One-Hour Glucose: 117. Group B strep has not been done as yet.""")

Results

+-----+---------+
|chunk|ner_label|
+-----+---------+
|CBC  |ABBR     |
|AB   |ABBR     |
|VDRL |ABBR     |
|HIV  |ABBR     |
+-----+---------+

Model Information

Model Name: ner_abbreviation_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