Mapping UMLS Codes with Their Corresponding ICD10CM Codes

Description

This model maps UMLS codes to ICD-10-CM codes. It is trained on the 2026AA release of the Unified Medical Language System (UMLS) dataset.

Live Demo Open in Colab Copy S3 URI

How to use


document_assembler = DocumentAssembler()\
    .setInputCol("text")\
    .setOutputCol("doc")

doc2chunk = Doc2Chunk()\
    .setInputCols(["doc"])\
    .setOutputCol("ner_chunk")

mapper = ChunkMapperModel.pretrained("umls_icd10cm_mapper","en","clinical/models")\
    .setInputCols(["ner_chunk"])\
    .setOutputCol("mappings")

pipeline = Pipeline(stages=[document_assembler, doc2chunk, mapper])
data = spark.createDataFrame([["C0011849"],["C0003873"],["C0042963"]]).toDF("text")
result = pipeline.fit(data).transform(data)


document_assembler = nlp.DocumentAssembler()\
    .setInputCol("text")\
    .setOutputCol("doc")

doc2chunk = nlp.Doc2Chunk()\
    .setInputCols(["doc"])\
    .setOutputCol("ner_chunk")

mapper = medical.ChunkMapperModel.pretrained("umls_icd10cm_mapper","en","clinical/models")\
    .setInputCols(["ner_chunk"])\
    .setOutputCol("mappings")

pipeline = nlp.Pipeline(stages=[document_assembler, doc2chunk, mapper])
data = spark.createDataFrame([["C0011849"],["C0003873"],["C0042963"]]).toDF("text")
result = pipeline.fit(data).transform(data)


val documentAssembler = new DocumentAssembler()
  .setInputCol("text")
  .setOutputCol("doc")

val doc2chunk = new Doc2Chunk()
  .setInputCols(Array("doc"))
  .setOutputCol("ner_chunk")

val mapper = ChunkMapperModel.pretrained("umls_icd10cm_mapper","en","clinical/models")
  .setInputCols(Array("ner_chunk"))
  .setOutputCol("mappings")

val pipeline = new Pipeline().setStages(Array(documentAssembler, doc2chunk, mapper))
val data = Seq("C0011849","C0003873","C0042963").toDF("text")
val result = pipeline.fit(data).transform(data)

Results

| umls_code   | icd10cm_code   |
|:------------|:---------------|
| C0011849    | E08-E13        |
| C0003873    | M06.9          |
| C0042963    | R11.10         |

Model Information

Model Name: umls_icd10cm_mapper
Compatibility: Healthcare NLP 6.4.0+
License: Licensed
Edition: Official
Input Labels: [ner_chunk]
Output Labels: [mappings]
Language: en
Size: 1.5 MB