Pipeline to Detect PHI for Deidentification (Augmented)

Description

This pretrained pipeline is built on the top of ner_deid_synthetic model.

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How to use

from sparknlp.pretrained import PretrainedPipeline

pipeline = PretrainedPipeline("ner_deid_synthetic_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_synthetic_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 | NAME        |     0.85705  |
|  2 | Hendrickson Ora               |      55 |    69 | NAME        |     0.8646   |
|  3 | 7194334                       |      78 |    84 | ID          |     1        |
|  4 | 01/13/93                      |      93 |   100 | DATE        |     1        |
|  5 | Oliveira                      |     110 |   117 | NAME        |     0.9998   |
|  6 | 25                            |     121 |   122 | AGE         |     0.9951   |
|  7 | 2079-11-09                    |     150 |   159 | DATE        |     0.9999   |
|  8 | Cocke County Baptist Hospital |     163 |   191 | LOCATION    |     0.968825 |
|  9 | 0295 Keats Street             |     195 |   211 | LOCATION    |     0.7831   |
| 10 | 302-786-5227                  |     221 |   232 | CONTACT     |     0.9985   |

Model Information

Model Name: ner_deid_synthetic_pipeline
Type: pipeline
Compatibility: Healthcare NLP 4.3.0+
License: Licensed
Edition: Official
Language: en
Size: 1.7 GB

Included Models

  • DocumentAssembler
  • SentenceDetectorDLModel
  • TokenizerModel
  • WordEmbeddingsModel
  • MedicalNerModel
  • NerConverterInternalModel