Pipeline to Detect PHI for Generic Deidentification in Romanian

Description

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

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How to use

from sparknlp.pretrained import PretrainedPipeline

pipeline = PretrainedPipeline("ner_deid_generic_pipeline", "ro", "clinical/models")

text = '''Spitalul Pentru Ochi de Deal, Drumul Oprea Nr. 972 Vaslui,737405 România
Tel: +40(235)413773
Data setului de analize: 25 May 2022 15:36:00
Nume si Prenume : BUREAN MARIA, Varsta: 77
Medic : Agota Evelyn Tımar
C.N.P : 2450502264401'''

result = pipeline.fullAnnotate(text)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline

val pipeline = new PretrainedPipeline("ner_deid_generic_pipeline", "ro", "clinical/models")

val text = "Spitalul Pentru Ochi de Deal, Drumul Oprea Nr. 972 Vaslui,737405 România
Tel: +40(235)413773
Data setului de analize: 25 May 2022 15:36:00
Nume si Prenume : BUREAN MARIA, Varsta: 77
Medic : Agota Evelyn Tımar
C.N.P : 2450502264401"

val result = pipeline.fullAnnotate(text)

Results

|    | ner_chunks                   |   begin |   end | ner_label   |   confidence |
|---:|:-----------------------------|--------:|------:|:------------|-------------:|
|  0 | Spitalul Pentru Ochi de Deal |       0 |    27 | LOCATION    |     0.88326  |
|  1 | Drumul Oprea Nr. 972         |      30 |    49 | LOCATION    |     0.98642  |
|  2 | Vaslui,737405 România        |      51 |    71 | LOCATION    |     0.8018   |
|  3 | +40(235)413773               |      78 |    91 | CONTACT     |     1        |
|  4 | 25 May 2022                  |     118 |   128 | DATE        |     1        |
|  5 | BUREAN MARIA                 |     157 |   168 | NAME        |     0.99965  |
|  6 | 77                           |     179 |   180 | AGE         |     1        |
|  7 | Agota Evelyn Tımar           |     190 |   207 | NAME        |     0.832933 |
|  8 | 2450502264401                |     217 |   229 | ID          |     1        |

Model Information

Model Name: ner_deid_generic_pipeline
Type: pipeline
Compatibility: Healthcare NLP 4.3.0+
License: Licensed
Edition: Official
Language: ro
Size: 1.2 GB

Included Models

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