Description
This pretrained pipeline is built on the top of ner_supplement_clinical model.
Predicted Entities
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("ner_supplement_clinical_pipeline", "en", "clinical/models")
text = '''Excellent!. The state of health improves, nervousness disappears, and night sleep improves. It also promotes hair and nail growth. I recommend :'''
result = pipeline.fullAnnotate(text)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("ner_supplement_clinical_pipeline", "en", "clinical/models")
val text = "Excellent!. The state of health improves, nervousness disappears, and night sleep improves. It also promotes hair and nail growth. I recommend :"
val result = pipeline.fullAnnotate(text)
Results
| | ner_chunks | begin | end | ner_label | confidence |
|---:|:-------------|--------:|------:|:------------|-------------:|
| 0 | nervousness | 42 | 52 | CONDITION | 0.9999 |
| 1 | night sleep | 70 | 80 | BENEFIT | 0.80775 |
| 2 | hair | 109 | 112 | BENEFIT | 0.9997 |
| 3 | nail growth | 118 | 128 | BENEFIT | 0.9997 |
Model Information
| Model Name: | ner_supplement_clinical_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 4.4.4+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 1.7 GB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- WordEmbeddingsModel
- MedicalNerModel
- NerConverterInternalModel