Description
This pipeline is designed to extract all entities mappable to HGNC codes.
How to use
from sparknlp.pretrained import PretrainedPipeline
ner_pipeline = PretrainedPipeline("ner_hgnc_pipeline", "en", "clinical/models")
result = ner_pipeline.annotate("""During today's consultation, we reviewed the results of the comprehensive genetic analysis performed on the patient.
This analysis uncovered complex interactions between several genes: DUX4, DUX4L20, FBXO48, MYOD1, and PAX7.
These findings are significant as they provide new understanding of the molecular pathways that are involved in muscle differentiation and may play a role in the development and progression of muscular dystrophies in this patient.""")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val ner_pipeline = PretrainedPipeline("ner_hgnc_pipeline", "en", "clinical/models")
val result = ner_pipeline.annotate("""During today's consultation, we reviewed the results of the comprehensive genetic analysis performed on the patient.
This analysis uncovered complex interactions between several genes: DUX4, DUX4L20, FBXO48, MYOD1, and PAX7.
These findings are significant as they provide new understanding of the molecular pathways that are involved in muscle differentiation and may play a role in the development and progression of muscular dystrophies in this patient.""")
Results
| | chunks | begin | end | entities |
|---:|:---------|--------:|------:|:-----------|
| 0 | DUX4 | 187 | 190 | GENE |
| 1 | DUX4L20 | 193 | 199 | GENE |
| 2 | FBXO48 | 202 | 207 | GENE |
| 3 | MYOD1 | 210 | 214 | GENE |
| 4 | PAX7 | 221 | 224 | GENE |
Model Information
| Model Name: | ner_hgnc_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