Description
This pretrained pipeline is built on the top of ner_oncology_anatomy_general_langtest model.
How to use
from sparknlp.pretrained import PretrainedPipeline
ner_pipeline = PretrainedPipeline("ner_oncology_anatomy_general_langtest_pipeline", "en", "clinical/models")
result = ner_pipeline.annotate("""The patient presented a mass in her left breast, and a possible metastasis in her lungs and in her liver.""")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val ner_pipeline = PretrainedPipeline("ner_oncology_anatomy_general_langtest_pipeline", "en", "clinical/models")
val result = ner_pipeline.annotate("""The patient presented a mass in her left breast, and a possible metastasis in her lungs and in her liver.""")
Results
| | chunks | begin | end | entities |
|---:|:---------|--------:|------:|:----------------|
| 0 | left | 36 | 39 | Direction |
| 1 | breast | 41 | 46 | Anatomical_Site |
| 2 | lungs | 82 | 86 | Anatomical_Site |
| 3 | liver | 99 | 103 | Anatomical_Site |
Model Information
| Model Name: | ner_oncology_anatomy_general_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