Description
A pipeline containing multiple models to identify Adverse Drug Events in clinical and free text.
Live Demo Open in Colab Copy S3 URI
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline('explain_clinical_doc_ade', 'en', 'clinical/models')
res = pipeline.fullAnnotate('The clinical course suggests that the interstitial pneumonitis was induced by hydroxyurea.')
val era_pipeline = new PretrainedPipeline("explain_clinical_doc_era", "en", "clinical/models")
val result = era_pipeline.fullAnnotate("""The clinical course suggests that the interstitial pneumonitis was induced by hydroxyurea.""")(0)
Results
| # | chunks | entities | assertion |
|----|-------------------------------|------------|------------|
| 0 | interstitial pneumonitis | ADE | Present |
| 1 | hydroxyurea | DRUG | Present |
Model Information
| Model Name: | explain_clinical_doc_ade |
| Type: | pipeline |
| Compatibility: | Spark NLP 2.7.3+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
Included Models
biobert_pubmed_base_cased, classifierdl_ade_conversational_biobert, ner_ade_biobert , assertion_dl_biobert