Description
This pretrained pipeline is built on the top of ner_oncology model.
Predicted Entities
Adenopathy, Age, Biomarker, Biomarker_Result, Cancer_Dx, Cancer_Score, Cancer_Surgery, Chemotherapy, Cycle_Count, Cycle_Day, Cycle_Number, Date, Death_Entity, Direction, Dosage, Duration, Frequency, Gender, Grade, Histological_Type, Hormonal_Therapy, Imaging_Test, Immunotherapy, Invasion, Line_Of_Therapy, Metastasis, Oncogene, Pathology_Result, Pathology_Test, Performance_Status, Race_Ethnicity, Radiation_Dose, Radiotherapy, Relative_Date, Response_To_Treatment, Route, Site_Bone, Site_Brain, Site_Breast, Site_Liver, Site_Lung, Site_Lymph_Node, Site_Other_Body_Part, Smoking_Status, Staging, Targeted_Therapy, Tumor_Finding, Tumor_Size, Unspecific_Therapy
How to use
from sparknlp.pretrained import PretrainedPipeline
ner_pipeline = PretrainedPipeline("ner_oncology_pipeline", "en", "clinical/models")
result = ner_pipeline.annotate("""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 the residual breast.
The cancer recurred as a right lung metastasis 13 years later. He underwent a regimen consisting of adriamycin (60 mg/m2) and cyclophosphamide (600 mg/m2) over six courses, as first line therapy.""")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val ner_pipeline = PretrainedPipeline("ner_oncology_pipeline", "en", "clinical/models")
val result = ner_pipeline.annotate("""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 the residual breast.
The cancer recurred as a right lung metastasis 13 years later. He underwent a regimen consisting of adriamycin (60 mg/m2) and cyclophosphamide (600 mg/m2) over six courses, as first line therapy.""")
Results
| | chunks | begin | end | entities |
|---:|:-------------------------------|--------:|------:|:----------------------|
| 0 | left | 31 | 34 | Direction |
| 1 | mastectomy | 36 | 45 | Cancer_Surgery |
| 2 | axillary lymph node dissection | 54 | 83 | Cancer_Surgery |
| 3 | left | 91 | 94 | Direction |
| 4 | breast cancer | 96 | 108 | Cancer_Dx |
| 5 | twenty years ago | 110 | 125 | Relative_Date |
| 6 | tumor | 132 | 136 | Tumor_Finding |
| 7 | positive | 142 | 149 | Biomarker_Result |
| 8 | ER | 155 | 156 | Biomarker |
| 9 | PR | 162 | 163 | Biomarker |
| 10 | radiotherapy | 183 | 194 | Radiotherapy |
| 11 | breast | 229 | 234 | Site_Breast |
| 12 | cancer | 241 | 246 | Cancer_Dx |
| 13 | recurred | 248 | 255 | Response_To_Treatment |
| 14 | right | 262 | 266 | Direction |
| 15 | lung | 268 | 271 | Site_Lung |
| 16 | metastasis | 273 | 282 | Metastasis |
| 17 | 13 years later | 284 | 297 | Relative_Date |
| 18 | He | 300 | 301 | Gender |
| 19 | adriamycin | 337 | 346 | Chemotherapy |
| 20 | 60 mg/m2 | 349 | 356 | Dosage |
| 21 | cyclophosphamide | 363 | 378 | Chemotherapy |
| 22 | 600 mg/m2 | 381 | 389 | Dosage |
| 23 | six courses | 397 | 407 | Cycle_Count |
| 24 | first line | 413 | 422 | Line_Of_Therapy |
Model Information
| Model Name: | ner_oncology_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 5.2.0+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 1.7 GB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- WordEmbeddingsModel
- MedicalNerModel
- NerConverter