Description
This pipeline maps ICD10-CM codes to their corresponding SNOMED codes via a direct dictionary lookup.
Wraps the icd10cm_snomed_mapper_20260901 mapper, trained on SNOMED CT US Edition 20260901 crosswalk data.
Live Demo Open in Colab Copy S3 URI
How to use
from sparknlp.pretrained import PretrainedPipeline
snomed_pipeline = PretrainedPipeline("icd10cm_snomed_mapping_pipeline_20260901", "en", "clinical/models")
data = spark.createDataFrame([["A02.20"]]).toDF("text")
result = snomed_pipeline.transform(data)
from johnsnowlabs import nlp, medical
snomed_pipeline = nlp.PretrainedPipeline("icd10cm_snomed_mapping_pipeline_20260901", "en", "clinical/models")
data = spark.createDataFrame([["A02.20"]]).toDF("text")
result = snomed_pipeline.transform(data)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val snomed_pipeline = PretrainedPipeline("icd10cm_snomed_mapping_pipeline_20260901", "en", "clinical/models")
val data = Seq("A02.20").toDF("text")
val result = snomed_pipeline.transform(data)
Results
| icd10cm_code | snomed_code | all_k_resolutions |
|:---------------|--------------:|:----------------------------------------------------------------------------------------------------------------------------------|
| A02.20 | 47375003 | 47375003::: |
| A00.0 | 240349003 | 240349003:::447282003:::63650001 |
| Z83.3 | 160303001 | 160303001:::160402005:::416855002:::430678008:::430679000:::444094009:::444161008:::704144000:::719761003:::719763000:::721151003 |
Model Information
| Model Name: | icd10cm_snomed_mapping_pipeline_20260901 |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 6.4.1+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 1.3 MB |
Included Models
- DocumentAssembler
- Doc2Chunk
- ChunkMapperModel