Description
This pretrained pipeline is built on the top of bert_token_classifier_ner_bc5cdr_disease model.
Predicted Entities
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("bert_token_classifier_ner_bc5cdr_disease_pipeline", "en", "clinical/models")
text = '''Indomethacin resulted in histopathologic findings typical of interstitial cystitis, such as leaky bladder epithelium and mucosal mastocytosis. The true incidence of nonsteroidal anti-inflammatory drug-induced cystitis in humans must be clarified by prospective clinical trials. An open-label phase II study of low-dose thalidomide in androgen-independent prostate cancer.'''
result = pipeline.fullAnnotate(text)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("bert_token_classifier_ner_bc5cdr_disease_pipeline", "en", "clinical/models")
val text = "Indomethacin resulted in histopathologic findings typical of interstitial cystitis, such as leaky bladder epithelium and mucosal mastocytosis. The true incidence of nonsteroidal anti-inflammatory drug-induced cystitis in humans must be clarified by prospective clinical trials. An open-label phase II study of low-dose thalidomide in androgen-independent prostate cancer."
val result = pipeline.fullAnnotate(text)
Results
| | ner_chunk | begin | end | ner_label | confidence |
|---:|:----------------------|--------:|------:|:------------|-------------:|
| 0 | interstitial cystitis | 61 | 81 | DISEASE | 0.999746 |
| 1 | mastocytosis | 129 | 140 | DISEASE | 0.999132 |
| 2 | cystitis | 209 | 216 | DISEASE | 0.999912 |
| 3 | prostate cancer | 355 | 369 | DISEASE | 0.999781 |
Model Information
Model Name: | bert_token_classifier_ner_bc5cdr_disease_pipeline |
Type: | pipeline |
Compatibility: | Healthcare NLP 4.4.4+ |
License: | Licensed |
Edition: | Official |
Language: | en |
Size: | 404.8 MB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- MedicalBertForTokenClassifier
- NerConverterInternalModel