Description
This pretrained pipeline is built on the top of ner_deid_subentity_glove model.
Predicted Entities
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("ner_deid_subentity_glove_pipeline", "en", "clinical/models")
text = '''Record date : 2093-01-13 , David Hale , M.D . , Name : Hendrickson Ora , MR # 7194334 Date : 01/13/93 . PCP : Oliveira , 25 years old , Record date : 2079-11-09 . Cocke County Baptist Hospital , 0295 Keats Street , Phone 302-786-5227.'''
result = pipeline.fullAnnotate(text)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("ner_deid_subentity_glove_pipeline", "en", "clinical/models")
val text = "Record date : 2093-01-13 , David Hale , M.D . , Name : Hendrickson Ora , MR # 7194334 Date : 01/13/93 . PCP : Oliveira , 25 years old , Record date : 2079-11-09 . Cocke County Baptist Hospital , 0295 Keats Street , Phone 302-786-5227."
val result = pipeline.fullAnnotate(text)
Results
| | ner_chunks | begin | end | ner_label | confidence |
|---:|:------------------------------|--------:|------:|:--------------|-------------:|
| 0 | 2093-01-13 | 14 | 23 | DATE | 1 |
| 1 | David Hale | 27 | 36 | DOCTOR | 0.99 |
| 2 | Hendrickson Ora | 55 | 69 | PATIENT | 0.60755 |
| 3 | 7194334 | 78 | 84 | MEDICALRECORD | 0.9993 |
| 4 | 01/13/93 | 93 | 100 | DATE | 1 |
| 5 | Oliveira | 110 | 117 | DOCTOR | 0.9082 |
| 6 | 25 | 121 | 122 | AGE | 0.9665 |
| 7 | 2079-11-09 | 150 | 159 | DATE | 1 |
| 8 | Cocke County Baptist Hospital | 163 | 191 | HOSPITAL | 0.731325 |
| 9 | 0295 Keats Street | 195 | 211 | STREET | 0.737067 |
| 10 | 302-786-5227 | 221 | 232 | PHONE | 0.9882 |
Model Information
Model Name: | ner_deid_subentity_glove_pipeline |
Type: | pipeline |
Compatibility: | Healthcare NLP 4.4.4+ |
License: | Licensed |
Edition: | Official |
Language: | en |
Size: | 167.4 MB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- WordEmbeddingsModel
- MedicalNerModel
- NerConverterInternalModel