Description
This pretrained pipeline is built on the top of bert_token_classifier_ner_pathogen model.
Predicted Entities
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("bert_token_classifier_ner_pathogen_pipeline", "en", "clinical/models")
text = '''Racecadotril is an antisecretory medication and it has better tolerability than loperamide. Diarrhea is the condition of having loose, liquid or watery bowel movements each day. Signs of dehydration often begin with loss of the normal stretchiness of the skin. This can progress to loss of skin color, a fast heart rate as it becomes more severe; while it has been speculated that rabies virus, Lyssavirus and Ephemerovirus could be transmitted through aerosols, studies have concluded that this is only feasible in limited conditions.'''
result = pipeline.fullAnnotate(text)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("bert_token_classifier_ner_pathogen_pipeline", "en", "clinical/models")
val text = "Racecadotril is an antisecretory medication and it has better tolerability than loperamide. Diarrhea is the condition of having loose, liquid or watery bowel movements each day. Signs of dehydration often begin with loss of the normal stretchiness of the skin. This can progress to loss of skin color, a fast heart rate as it becomes more severe; while it has been speculated that rabies virus, Lyssavirus and Ephemerovirus could be transmitted through aerosols, studies have concluded that this is only feasible in limited conditions."
val result = pipeline.fullAnnotate(text)
Results
| | ner_chunk | begin | end | ner_label | confidence |
|---:|:----------------|--------:|------:|:-----------------|-------------:|
| 0 | Racecadotril | 0 | 11 | Medicine | 0.986453 |
| 1 | loperamide | 80 | 89 | Medicine | 0.967653 |
| 2 | Diarrhea | 92 | 99 | MedicalCondition | 0.92107 |
| 3 | loose | 128 | 132 | MedicalCondition | 0.639717 |
| 4 | liquid | 135 | 140 | MedicalCondition | 0.739769 |
| 5 | watery | 145 | 150 | MedicalCondition | 0.911771 |
| 6 | bowel movements | 152 | 166 | MedicalCondition | 0.637392 |
| 7 | dehydration | 187 | 197 | MedicalCondition | 0.81079 |
| 8 | loss | 282 | 285 | MedicalCondition | 0.526605 |
| 9 | color | 295 | 299 | MedicalCondition | 0.612506 |
| 10 | fast | 304 | 307 | MedicalCondition | 0.555894 |
| 11 | heart rate | 309 | 318 | MedicalCondition | 0.486794 |
| 12 | rabies virus | 381 | 392 | Pathogen | 0.738198 |
| 13 | Lyssavirus | 395 | 404 | Pathogen | 0.979239 |
| 14 | Ephemerovirus | 410 | 422 | Pathogen | 0.992292 |
Model Information
| Model Name: | bert_token_classifier_ner_pathogen_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