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  • John Snow Labs
  • Jul 28, 2025

HPO Code To UMLS Code Mapping

  • licensed
  • en
  • umls
  • hpo
  • mapping

Description

This pretrained model maps HPO codes to corresponding UMLS codes. It also returns all the possible UMLS codes in the all_k_resolutions in the metadata.

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How to use


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

chunk_assembler = Doc2Chunk()\
      .setInputCols(["document"])\
      .setOutputCol("hpo_code")

mapperModel = ChunkMapperModel.pretrained("hpo_umls_mapper", "en", "clinical/models")\
    .setInputCols(["hpo_code"])\
    .setOutputCol("mappings")\
    .setRels(["umls_code"])

mapper_pipeline = Pipeline(stages=[
    document_assembler,
    chunk_assembler,
    mapperModel
])

data = spark.createDataFrame([["HP:0000010"],["HP:0200039"],["HP:0000951"]]).toDF("text")
result = mapper_pipeline.fit(data).transform(data)



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

chunk_assembler = nlp.Doc2Chunk()\
      .setInputCols(["document"])\
      .setOutputCol("hpo_code")

mapperModel = medical.ChunkMapperModel.pretrained("hpo_umls_mapper", "en", "clinical/models")\
    .setInputCols(["hpo_code"])\
    .setOutputCol("mappings")\
    .setRels(["umls_code"])

mapper_pipeline = nlp.Pipeline(stages=[
    document_assembler,
    chunk_assembler,
    mapperModel
])

data = spark.createDataFrame([["HP:0000010"],["HP:0200039"],["HP:0000951"]]).toDF("text")
result = mapper_pipeline.fit(data).transform(data)



val ocument_assembler = new DocumentAssembler()
      .setInputCol("text")
      .setOutputCol("document")

val chunk_assembler = new Doc2Chunk()
      .setInputCols("document")
      .setOutputCol("hpo_code")

val mapperModel = ChunkMapperModel.pretrained("hpo_umls_mapper", "en", "clinical/models")
    .setInputCols("hpo_code")
    .setOutputCol("mappings")
    .setRels(Array("umls_code"))

val mapper_pipeline = new Pipeline().setStages(Array(
    document_assembler,
    chunk_assembler,
    mapperModel
))

val data = Seq("HP:0000010", "HP:0200039", "HP:0000951").toDF("text")

val result = mapper_pipeline.fit(data).transform(data)

Results


+----------+---------+-----------------------------------------+
|  hpo_code|umls_code|                        all_k_resolutions|
+----------+---------+-----------------------------------------+
|HP:0000010| C0262421|C0262421:::C0262655:::C0034186:::C0520575|
|HP:0200039| C0877055|           C0877055:::C0152081:::C0241157|
|HP:0000951| C0037268|C0037268:::C0241164:::C0043345:::C0038325|
+----------+---------+-----------------------------------------+

Model Information

Model Name: hpo_umls_mapper
Compatibility: Healthcare NLP 6.0.4+
License: Licensed
Edition: Official
Input Labels: [ner_chunk]
Output Labels: [mappings]
Language: en
Size: 27.7 KB