Description
This pretrained pipeline is built on the top of ner_oncology_therapy model.
Predicted Entities
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("ner_oncology_therapy_pipeline", "en", "clinical/models")
text = '''The had previously undergone a left mastectomy and an axillary lymph node dissection for a left breast cancer twenty years ago.
The tumor was positive for ER and PR. Postoperatively, radiotherapy was administered to her breast.
The cancer recurred as a right lung metastasis 13 years later. The patient underwent a regimen consisting of adriamycin (60 mg/m2) and cyclophosphamide (600 mg/m2) over six courses, as first line therapy.'''
result = pipeline.fullAnnotate(text)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("ner_oncology_therapy_pipeline", "en", "clinical/models")
val text = "The had previously undergone a left mastectomy and an axillary lymph node dissection for a left breast cancer twenty years ago.
The tumor was positive for ER and PR. Postoperatively, radiotherapy was administered to her breast.
The cancer recurred as a right lung metastasis 13 years later. The patient underwent a regimen consisting of adriamycin (60 mg/m2) and cyclophosphamide (600 mg/m2) over six courses, as first line therapy."
val result = pipeline.fullAnnotate(text)
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("ner_oncology_therapy_pipeline", "en", "clinical/models")
text = '''The had previously undergone a left mastectomy and an axillary lymph node dissection for a left breast cancer twenty years ago.
The tumor was positive for ER and PR. Postoperatively, radiotherapy was administered to her breast.
The cancer recurred as a right lung metastasis 13 years later. The patient underwent a regimen consisting of adriamycin (60 mg/m2) and cyclophosphamide (600 mg/m2) over six courses, as first line therapy.'''
result = pipeline.fullAnnotate(text)
Results
| | ner_chunks | begin | end | ner_label | confidence |
|---:|:-------------------------------|--------:|------:|:----------------------|-------------:|
| 0 | mastectomy | 36 | 45 | Cancer_Surgery | 0.9817 |
| 1 | axillary lymph node dissection | 54 | 83 | Cancer_Surgery | 0.719725 |
| 2 | radiotherapy | 183 | 194 | Radiotherapy | 0.9984 |
| 3 | recurred | 239 | 246 | Response_To_Treatment | 0.9481 |
| 4 | adriamycin | 337 | 346 | Chemotherapy | 0.9981 |
| 5 | 60 mg/m2 | 349 | 356 | Dosage | 0.58815 |
| 6 | cyclophosphamide | 363 | 378 | Chemotherapy | 0.9976 |
| 7 | 600 mg/m2 | 381 | 389 | Dosage | 0.64205 |
| 8 | six courses | 397 | 407 | Cycle_Count | 0.46815 |
| 9 | first line | 413 | 422 | Line_Of_Therapy | 0.95015 |
Model Information
| Model Name: | ner_oncology_therapy_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