NER Pipeline for Clinical Department - Voice of the Patient

Description

This pipeline extracts mentions of clinical departments and medical devices from health-related text in colloquial language.

Predicted Entities

Live Demo Open in Colab Copy S3 URI

How to use

from sparknlp.pretrained import PretrainedPipeline

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

pipeline.annotate("
My little brother is having surgery tomorrow in the orthopedic department. He is getting a titanium plate put in his leg to help it heal faster. Wishing him a speedy recovery!
")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline

val pipeline = new PretrainedPipeline("ner_vop_clinical_dept_pipeline", "en", "clinical/models")

val result = pipeline.annotate("
My little brother is having surgery tomorrow in the orthopedic department. He is getting a titanium plate put in his leg to help it heal faster. Wishing him a speedy recovery!
")

Results

| chunk                 | ner_label     |
|:----------------------|:--------------|
| orthopedic department | ClinicalDept  |
| titanium plate        | MedicalDevice |

Model Information

Model Name: ner_vop_clinical_dept_pipeline
Type: pipeline
Compatibility: Healthcare NLP 4.4.4+
License: Licensed
Edition: Official
Language: en
Size: 791.7 MB

Included Models

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