Snomed to ICD10 Code Mapping


This pretrained pipeline maps SNOMED codes to ICD10CM codes without using any text data. You’ll just feed a comma or white space delimited SNOMED codes and it will return the corresponding candidate ICD10CM codes as a list (multiple ICD10 codes for each Snomed code). For the time being, it supports 132K Snomed codes and 30K ICD10 codes and will be augmented & enriched in the next releases.


How to use

from sparknlp.pretrained import PretrainedPipeline 
pipeline = PretrainedPipeline( "snomed_icd10cm_mapping","en","clinical/models")
pipeline.annotate('721617001 733187009 109006')
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("icd10cm_snomed_mapping","en","clinical/models")
val result = pipeline.annotate('721617001 733187009 109006')


{'snomed': ['721617001', '733187009', '109006'],
 'icd10cm': ['K22.70, C15.5',
  'M89.59, M89.50, M96.89',
  'F41.9, F40.10, F94.8, F93.0, F40.8, F93.8']}

Model Information

Model Name: snomed_icd10cm_mapping
Type: pipeline
Compatibility: Spark NLP 2.7.5+
License: Licensed
Edition: Official
Language: en

Included Models

  • DocumentAssembler
  • TokenizerModel
  • LemmatizerModel
  • Finisher