ICD10 to Snomed Code Mapping

Description

This pretrained pipeline maps ICD10CM codes to SNOMED codes without using any text data. You’ll just feed a comma or white space delimited ICD10CM codes and it will return the corresponding SNOMED codes as a list. For the time being, it supports 132K Snomed codes and will be augmented & enriched in the next releases.

Live Demo Download

How to use

from sparknlp.pretrained import PretrainedPipeline 
pipeline = PretrainedPipeline( "icd10cm_snomed_mapping","en","clinical/models")
pipeline.annotate('M89.50 I288 H16269')
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("icd10cm_snomed_mapping","en","clinical/models")
val result = pipeline.annotate('M89.50 I288 H16269')

Results

{'icd10cm': ['M89.50', 'I288', 'H16269'],
 'snomed': ['733187009', '449433008', '51264003']}

Model Information

Model Name: icd10cm_snomed_mapping
Type: pipeline
Compatibility: Spark NLP for Healthcare 2.7.5+
License: Licensed
Edition: Official
Language: en

Included Models

  • DocumentAssembler
  • TokenizerModel
  • LemmatizerModel
  • Finisher