Description
This pretrained pipeline is built on the top of jsl_rd_ner_wip_greedy_biobert model.
How to use
pipeline = PretrainedPipeline("jsl_rd_ner_wip_greedy_biobert_pipeline", "en", "clinical/models")
pipeline.annotate("Bilateral breast ultrasound was subsequently performed, which demonstrated an ovoid mass measuring approximately 0.5 x 0.5 x 0.4 cm in diameter located within the anteromedial aspect of the left shoulder. This mass demonstrates isoechoic echotexture to the adjacent muscle, with no evidence of internal color flow. This may represent benign fibrous tissue or a lipoma.")
val pipeline = new PretrainedPipeline("jsl_rd_ner_wip_greedy_biobert_pipeline", "en", "clinical/models")
pipeline.annotate("Bilateral breast ultrasound was subsequently performed, which demonstrated an ovoid mass measuring approximately 0.5 x 0.5 x 0.4 cm in diameter located within the anteromedial aspect of the left shoulder. This mass demonstrates isoechoic echotexture to the adjacent muscle, with no evidence of internal color flow. This may represent benign fibrous tissue or a lipoma.")
import nlu
nlu.load("en.med_ner.wip_greedy_biobert.pipeline").predict("""Bilateral breast ultrasound was subsequently performed, which demonstrated an ovoid mass measuring approximately 0.5 x 0.5 x 0.4 cm in diameter located within the anteromedial aspect of the left shoulder. This mass demonstrates isoechoic echotexture to the adjacent muscle, with no evidence of internal color flow. This may represent benign fibrous tissue or a lipoma.""")
Results
| | chunk | entity |
|---:|:----------------------|:--------------------------|
| 0 | Bilateral | Direction |
| 1 | breast | BodyPart |
| 2 | ultrasound | ImagingTest |
| 3 | ovoid mass | ImagingFindings |
| 4 | 0.5 x 0.5 x 0.4 | Measurements |
| 5 | cm | Units |
| 6 | left | Direction |
| 7 | shoulder | BodyPart |
| 8 | mass | ImagingFindings |
| 9 | isoechoic echotexture | ImagingFindings |
| 10 | muscle | BodyPart |
| 11 | internal color flow | ImagingFindings |
| 12 | benign fibrous tissue | ImagingFindings |
| 13 | lipoma | Disease_Syndrome_Disorder |
Model Information
| Model Name: | jsl_rd_ner_wip_greedy_biobert_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 3.4.1+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 422.6 MB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- BertEmbeddings
- MedicalNerModel
- NerConverter