Pipeline to Detect Adverse Drug Events (healthcare)

Description

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

Predicted Entities

DRUG, ADE

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How to use

from sparknlp.pretrained import PretrainedPipeline

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

text = '''Been taking Lipitor for 15 years , have experienced severe fatigue a lot!!! . Doctor moved me to voltaren 2 months ago , so far , have only experienced cramps.'''

result = pipeline.fullAnnotate(text)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline

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

val text = "Been taking Lipitor for 15 years , have experienced severe fatigue a lot!!! . Doctor moved me to voltaren 2 months ago , so far , have only experienced cramps."

val result = pipeline.fullAnnotate(text)
import nlu
nlu.load("en.med_ner.healthcare_ade.pipeline").predict("""Been taking Lipitor for 15 years , have experienced severe fatigue a lot!!! . Doctor moved me to voltaren 2 months ago , so far , have only experienced cramps.""")

Results

|    | ner_chunks     |   begin |   end | ner_label   |   confidence |
|---:|:---------------|--------:|------:|:------------|-------------:|
|  0 | Lipitor        |      12 |    18 | DRUG        |      0.998   |
|  1 | severe fatigue |      52 |    65 | ADE         |      0.67055 |
|  2 | voltaren       |      97 |   104 | DRUG        |      0.9255  |
|  3 | cramps         |     152 |   157 | ADE         |      0.9392  |

Model Information

Model Name: ner_ade_healthcare_pipeline
Type: pipeline
Compatibility: Healthcare NLP 4.4.4+
License: Licensed
Edition: Official
Language: en
Size: 513.7 MB

Included Models

  • DocumentAssembler
  • SentenceDetectorDLModel
  • TokenizerModel
  • WordEmbeddingsModel
  • MedicalNerModel
  • NerConverterInternalModel