Description
This pretrained pipeline is built on the top of bert_token_classifier_ner_bc5cdr_chemicals model.
Predicted Entities
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("bert_token_classifier_ner_bc5cdr_chemicals_pipeline", "en", "clinical/models")
text = '''The possibilities that these cardiovascular findings might be the result of non-selective inhibition of monoamine oxidase or of amphetamine and metamphetamine are discussed. The results have shown that the degradation product p-choloroaniline is not a significant factor in chlorhexidine-digluconate associated erosive cystitis. A high percentage of kanamycin - colistin and povidone-iodine irrigations were associated with erosive cystitis and suggested a possible complication with human usage.'''
result = pipeline.fullAnnotate(text)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("bert_token_classifier_ner_bc5cdr_chemicals_pipeline", "en", "clinical/models")
val text = "The possibilities that these cardiovascular findings might be the result of non-selective inhibition of monoamine oxidase or of amphetamine and metamphetamine are discussed. The results have shown that the degradation product p-choloroaniline is not a significant factor in chlorhexidine-digluconate associated erosive cystitis. A high percentage of kanamycin - colistin and povidone-iodine irrigations were associated with erosive cystitis and suggested a possible complication with human usage."
val result = pipeline.fullAnnotate(text)
Results
| | ner_chunk | begin | end | ner_label | confidence |
|---:|:--------------------------|--------:|------:|:------------|-------------:|
| 0 | amphetamine | 128 | 138 | CHEM | 0.999973 |
| 1 | metamphetamine | 144 | 157 | CHEM | 0.999972 |
| 2 | p-choloroaniline | 226 | 241 | CHEM | 0.588953 |
| 3 | chlorhexidine-digluconate | 274 | 298 | CHEM | 0.999979 |
| 4 | kanamycin | 350 | 358 | CHEM | 0.999978 |
| 5 | colistin | 362 | 369 | CHEM | 0.999942 |
| 6 | povidone-iodine | 375 | 389 | CHEM | 0.999977 |
Model Information
| Model Name: | bert_token_classifier_ner_bc5cdr_chemicals_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