Description
This pipeline is designed to extract all entities mappable to NCI-t codes.
1 NER model and a Text Matcher are used to achieve those tasks.
How to use
from sparknlp.pretrained import PretrainedPipeline
ner_pipeline = PretrainedPipeline("ner_ncit_pipeline", "en", "clinical/models")
result = ner_pipeline.annotate("""
A 65-year-old woman had a history of debulking surgery, bilateral oophorectomy with omentectomy,
total hysterectomy with radical pelvic lymph nodes dissection due to ovarian carcinoma (mucinous-type carcinoma, stage Ic) 1 year ago.
Patient's medical compliance was poor and failed to complete her chemotherapy (cyclophosphamide 750 mg/m2, carboplatin 300 mg/m2).
Recently, she noted a palpable right breast mass, 15 cm in size which nearly occupied the whole right breast in 2 months. Core needle biopsy revealed metaplastic carcinoma.
""")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val ner_pipeline = PretrainedPipeline("ner_ncit_pipeline", "en", "clinical/models")
val result = ner_pipeline.annotate("""
A 65-year-old woman had a history of debulking surgery, bilateral oophorectomy with omentectomy,
total hysterectomy with radical pelvic lymph nodes dissection due to ovarian carcinoma (mucinous-type carcinoma, stage Ic) 1 year ago.
Patient's medical compliance was poor and failed to complete her chemotherapy (cyclophosphamide 750 mg/m2, carboplatin 300 mg/m2).
Recently, she noted a palpable right breast mass, 15 cm in size which nearly occupied the whole right breast in 2 months. Core needle biopsy revealed metaplastic carcinoma.
""")
Results
| | chunks | begin | end | entities |
|---:|:--------------------------------------|--------:|------:|:---------------|
| 0 | debulking surgery | 38 | 54 | Cancer_Surgery |
| 1 | bilateral oophorectomy | 57 | 78 | Cancer_Surgery |
| 2 | omentectomy | 85 | 95 | Cancer_Surgery |
| 3 | total hysterectomy | 99 | 116 | Cancer_Surgery |
| 4 | radical pelvic lymph nodes dissection | 123 | 159 | Cancer_Surgery |
| 5 | ovarian carcinoma | 168 | 184 | Cancer_dx |
| 6 | mucinous-type carcinoma | 187 | 209 | Cancer_dx |
| 7 | stage Ic | 212 | 219 | Staging |
| 8 | chemotherapy | 300 | 311 | Chemotherapy |
| 9 | cyclophosphamide | 314 | 329 | Chemotherapy |
| 10 | carboplatin | 342 | 352 | Chemotherapy |
| 11 | right | 398 | 402 | Direction |
| 12 | breast | 404 | 409 | Site_Breast |
| 13 | mass | 411 | 414 | Tumor_Finding |
| 14 | right | 463 | 467 | Direction |
| 15 | breast | 469 | 474 | Site_Breast |
| 16 | Core needle biopsy | 489 | 506 | Pathology_Test |
| 17 | metaplastic carcinoma | 517 | 537 | Cancer_dx |
Model Information
| Model Name: | ner_ncit_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 6.0.2+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 1.7 GB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- WordEmbeddingsModel
- MedicalNerModel
- NerConverterInternalModel
- TextMatcherInternalModel
- ChunkMergeModel