Description
This pretrained pipeline is built on the top of ner_oncology_demographics_langtest model.
How to use
from sparknlp.pretrained import PretrainedPipeline
ner_pipeline = PretrainedPipeline("ner_oncology_demographics_langtest_pipeline", "en", "clinical/models")
result = ner_pipeline.annotate("""The patient is a 40 year old man with history of heavy smoking.""")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val ner_pipeline = PretrainedPipeline("ner_oncology_demographics_langtest_pipeline", "en", "clinical/models")
val result = ner_pipeline.annotate("""The patient is a 40 year old man with history of heavy smoking.""")
Results
| | chunks | begin | end | entities |
|---:|:------------|--------:|------:|:---------------|
| 0 | 40 year old | 17 | 27 | Age |
| 1 | man | 29 | 31 | Gender |
| 2 | smoking | 55 | 61 | Smoking_Status |
Model Information
| Model Name: | ner_oncology_demographics_langtest_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 5.1.0+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 1.7 GB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- WordEmbeddingsModel
- MedicalNerModel
- NerConverter