Pipeline to Mapping ICD10-CM Codes with Their Corresponding ICD-9-CM Codes

Description

This pretrained pipeline is built on the top of icd10_icd9_mapper model.

Open in Colab Copy S3 URI

How to use

from sparknlp.pretrained import PretrainedPipeline

pipeline= PretrainedPipeline("icd10_icd9_mapping", "en", "clinical/models")

result= pipeline.fullAnnotate('Z833 A0100 A000')
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline

val pipeline= new PretrainedPipeline("icd10_icd9_mapping", "en", "clinical/models")

val result= pipeline.fullAnnotate('Z833 A0100 A000')
import nlu
nlu.load("en.icd10_icd9.mapping").predict("""Z833 A0100 A000""")

Results

|    | icd10_code          | icd9_code          |
|---:|:--------------------|:-------------------|
|  0 | Z833 | A0100 | A000 | V180 | 0020 | 0010 |

Model Information

Model Name: icd10_icd9_mapping
Type: pipeline
Compatibility: Healthcare NLP 4.1.0+
License: Licensed
Edition: Official
Language: en
Size: 589.5 KB

Included Models

  • DocumentAssembler
  • TokenizerModel
  • ChunkMapperModel