Description
This pretrained pipeline is built on the top of ner_oncology_response_to_treatment_langtest model.
How to use
from sparknlp.pretrained import PretrainedPipeline
ner_pipeline = PretrainedPipeline("ner_oncology_response_to_treatment_langtest_pipeline", "en", "clinical/models")
result = ner_pipeline.annotate("""She completed her first-line therapy, but some months later there was recurrence of the breast cancer.""")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val ner_pipeline = PretrainedPipeline("ner_oncology_response_to_treatment_langtest_pipeline", "en", "clinical/models")
val result = ner_pipeline.annotate("""She completed her first-line therapy, but some months later there was recurrence of the breast cancer.""")
Results
| | chunks | begin | end | entities |
|---:|:-----------|--------:|------:|:----------------------|
| 0 | first-line | 18 | 27 | Line_Of_Therapy |
| 1 | recurrence | 70 | 79 | Response_To_Treatment |
Model Information
| Model Name: | ner_oncology_response_to_treatment_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