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  • John Snow Labs
  • Jun 17, 2023

Pipeline to Mapping SNOMED Codes with Their Corresponding UMLS Codes

  • en
  • licensed
  • clinical
  • pipeline
  • chunk_mapping
  • snomed
  • umls

Description

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

Predicted Entities

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Available as Private API Endpoint

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How to use

from sparknlp.pretrained import PretrainedPipeline

pipeline = PretrainedPipeline("snomed_umls_mapping", "en", "clinical/models")
result = pipeline.fullAnnotate(["733187009", "449433008", "51264003"])

import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline

val pipeline = new PretrainedPipeline("snomed_umls_mapping", "en", "clinical/models")
val result = pipeline.fullAnnotate(["733187009", "449433008", "51264003"])

import nlu
nlu.load("en.snomed.umls.mapping").predict("""Put your text here.""")

Results

|   | snomed_code | umls_code |
|--:|------------:|----------:|
| 0 |   733187009 |  C4546029 |
| 1 |   449433008 |  C3164619 |
| 2 |    51264003 |  C0271267 |

Model Information

Model Name: snomed_umls_mapping
Type: pipeline
Compatibility: Healthcare NLP 4.4.4+
License: Licensed
Edition: Official
Language: en
Size: 5.1 MB

Included Models

  • DocumentAssembler
  • TokenizerModel
  • ChunkMapperModel