Description
This pretrained pipeline is built on the top of ner_deid_sd_large model.
Live Demo Open in Colab Copy S3 URI
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("ner_deid_sd_large_pipeline", "en", "clinical/models")
pipeline.annotate("""A. Record date : 2093-01-13, David Hale, M.D., Name : Hendrickson, Ora MR. # 7194334 Date : 01/13/93 PCP : Oliveira, 25-year-old, Record date : 1-11-2000. Cocke County Baptist Hospital. 0295 Keats Street. Phone +1 (302) 786-5227. Patient's complaints first surfaced when he started working for Brothers Coal-Mine.""")
val pipeline = new PretrainedPipeline("ner_deid_sd_large_pipeline", "en", "clinical/models")
pipeline.annotate("A. Record date : 2093-01-13, David Hale, M.D., Name : Hendrickson, Ora MR. # 7194334 Date : 01/13/93 PCP : Oliveira, 25-year-old, Record date : 1-11-2000. Cocke County Baptist Hospital. 0295 Keats Street. Phone +1 (302) 786-5227. Patient's complaints first surfaced when he started working for Brothers Coal-Mine.")
import nlu
nlu.load("en.deid.med_ner_large.pipeline").predict("""A. Record date : 2093-01-13, David Hale, M.D., Name : Hendrickson, Ora MR. # 7194334 Date : 01/13/93 PCP : Oliveira, 25-year-old, Record date : 1-11-2000. Cocke County Baptist Hospital. 0295 Keats Street. Phone +1 (302) 786-5227. Patient's complaints first surfaced when he started working for Brothers Coal-Mine.""")
Results
+-----------------------------+--------+
|chunks |entities|
+-----------------------------+--------+
|2093-01-13 |DATE |
|David Hale |NAME |
|Hendrickson, Ora |NAME |
|7194334 |ID |
|01/13/93 |DATE |
|Oliveira |NAME |
|1-11-2000 |DATE |
|Cocke County Baptist Hospital|LOCATION|
|0295 Keats Street |LOCATION|
|786-5227 |CONTACT |
|Brothers Coal-Mine |LOCATION|
+-----------------------------+--------+
Model Information
| Model Name: | ner_deid_sd_large_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 3.4.1+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 1.7 GB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- WordEmbeddingsModel
- MedicalNerModel
- NerConverter