Description
This pretrained pipeline is built on the top of ner_oncology_tnm model.
Predicted Entities
Cancer_Dx, Lymph_Node, Metastasis, Tumor_Description, Staging, Tumor, Lymph_Node_Modifier
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("ner_oncology_tnm_pipeline", "en", "clinical/models")
text = '''The final diagnosis was metastatic breast carcinoma, and it was classified as T2N1M1 stage IV. The histological grade of this 4 cm tumor was grade 2.'''
result = pipeline.fullAnnotate(text)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("ner_oncology_tnm_pipeline", "en", "clinical/models")
val text = "The final diagnosis was metastatic breast carcinoma, and it was classified as T2N1M1 stage IV. The histological grade of this 4 cm tumor was grade 2."
val result = pipeline.fullAnnotate(text)
Results
| | ner_chunks | begin | end | ner_label | confidence |
|---:|:-----------------|--------:|------:|:------------------|-------------:|
| 0 | metastatic | 24 | 33 | Metastasis | 0.9999 |
| 1 | breast carcinoma | 35 | 50 | Cancer_Dx | 0.9972 |
| 2 | T2N1M1 stage IV | 78 | 92 | Staging | 0.905267 |
| 3 | 4 cm | 126 | 129 | Tumor_Description | 0.85105 |
| 4 | tumor | 131 | 135 | Tumor | 0.9926 |
| 5 | grade 2 | 141 | 147 | Tumor_Description | 0.89705 |
Model Information
| Model Name: | ner_oncology_tnm_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 4.3.0+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 1.7 GB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- WordEmbeddingsModel
- MedicalNerModel
- NerConverterInternalModel