Pipeline to Detect Oncology-Specific Entities

Description

This pretrained pipeline is built on the top of ner_oncology model.

Copy S3 URI

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