Description
This pretrained pipeline is built on the top of ner_deidentify_dl model.
Predicted Entities
DATE, PATIENT, MEDICALRECORD, DOCTOR, AGE, HOSPITAL,STATE, CITY, PROFESSION, STREET, ZIP, PHONE, COUNTRY, ORGANIZATION, FAX, IDNUM, HEALTHPLAN, USERNAME, EMAIL, BIOID, LOCATION-OTHER, DEVICE, URL,ID
Live Demo Open in Colab Copy S3 URI
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("ner_deidentify_dl_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 month years-old , Record date : 2079-11-09 . Cocke County Baptist Hospital . 0295 Keats Street")
val pipeline = new PretrainedPipeline("ner_deidentify_dl_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 month years-old , Record date : 2079-11-09 . Cocke County Baptist Hospital . 0295 Keats Street")
import nlu
nlu.load("en.med_ner.deidentify.pipeline").predict("""A . Record date : 2093-01-13 , David Hale , M.D . , Name : Hendrickson , Ora MR . # 7194334 Date : 01/13/93 PCP : Oliveira , 25 month years-old , Record date : 2079-11-09 . Cocke County Baptist Hospital . 0295 Keats Street""")
Results
+---------------+-----+
|ner_label |count|
+---------------+-----+
|O |28 |
|I-HOSPITAL |4 |
|B-DATE |3 |
|I-STREET |3 |
|I-PATIENT |2 |
|B-DOCTOR |2 |
|B-AGE |1 |
|B-PATIENT |1 |
|I-DOCTOR |1 |
|B-MEDICALRECORD|1 |
+---------------+-----+.
+-----------------------------+-------------+
|chunk |ner_label |
+-----------------------------+-------------+
|2093-01-13 |DATE |
|David Hale |DOCTOR |
|Hendrickson , Ora |PATIENT |
|7194334 |MEDICALRECORD|
|01/13/93 |DATE |
|Oliveira |DOCTOR |
|25 |AGE |
|2079-11-09 |DATE |
|Cocke County Baptist Hospital|HOSPITAL |
|0295 Keats Street |STREET |
+-----------------------------+-------------+
Model Information
| Model Name: | ner_deidentify_dl_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