NER Pipeline for Tests - Voice of the Patient

Description

This pipeline extracts mentions of tests and their results 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_test_pipeline", "en", "clinical/models")

pipeline.annotate("
I went to the endocrinology department to get my thyroid levels checked. They ordered a blood test and found out that I have hypothyroidism, so now I'm on medication to manage it.
")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline

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

val result = pipeline.annotate("
I went to the endocrinology department to get my thyroid levels checked. They ordered a blood test and found out that I have hypothyroidism, so now I'm on medication to manage it.
")

Results

| chunk          | ner_label   |
|:---------------|:------------|
| thyroid levels | Test        |
| blood test     | Test        |

Model Information

Model Name: ner_vop_test_pipeline
Type: pipeline
Compatibility: Healthcare NLP 4.4.4+
License: Licensed
Edition: Official
Language: en
Size: 791.6 MB

Included Models

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