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.

Predicted Entities

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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("""Put your text here.""")

Results

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

Model Information

Model Name: icd10_icd9_mapping
Type: pipeline
Compatibility: Healthcare NLP 4.4.4+
License: Licensed
Edition: Official
Language: en
Size: 593.6 KB

Included Models

  • DocumentAssembler
  • TokenizerModel
  • ChunkMapperModel