Description
This model performs conversion of clinical entities and concepts from ICD-11 coding to their corresponding ICD-10 codes. Trained on the WHO ICD-11 2026-01 release.
Live Demo Open in Colab Copy S3 URI
How to use
document_assembler = DocumentAssembler()\
.setInputCol("text")\
.setOutputCol("document")
doc2chunk = Doc2Chunk()\
.setInputCols(["document"])\
.setOutputCol("ner_chunk")
icd11_icd10_mapper = ChunkMapperModel.pretrained("icd11_icd10_mapper_202601", "en", "clinical/models")\
.setInputCols(["ner_chunk"])\
.setOutputCol("mappings")
pipeline = Pipeline(stages=[document_assembler, doc2chunk, icd11_icd10_mapper])
data = spark.createDataFrame([[c] for c in ['1A00', '8A00.0', 'BA00.Z']], ["text"])
result = pipeline.fit(data).transform(data)
document_assembler = nlp.DocumentAssembler()\
.setInputCol("text")\
.setOutputCol("document")
doc2chunk = nlp.Doc2Chunk()\
.setInputCols(["document"])\
.setOutputCol("ner_chunk")
icd11_icd10_mapper = medical.ChunkMapperModel.pretrained("icd11_icd10_mapper_202601", "en", "clinical/models")\
.setInputCols(["ner_chunk"])\
.setOutputCol("mappings")
pipeline = nlp.Pipeline(stages=[document_assembler, doc2chunk, icd11_icd10_mapper])
data = spark.createDataFrame([[c] for c in ['1A00', '8A00.0', 'BA00.Z']], ["text"])
result = pipeline.fit(data).transform(data)
val documentAssembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")
val doc2chunk = new Doc2Chunk()
.setInputCols("document")
.setOutputCol("ner_chunk")
val icd11Icd10Mapper = ChunkMapperModel
.pretrained("icd11_icd10_mapper_202601", "en", "clinical/models")
.setInputCols(Array("ner_chunk"))
.setOutputCol("mappings")
val pipeline = new Pipeline().setStages(Array(documentAssembler, doc2chunk, icd11Icd10Mapper))
val data = Seq(['1A00', '8A00.0', 'BA00.Z']).toDF("text")
val result = pipeline.fit(data).transform(data)
Results
| icd11_code | icd10_code |
|:-------------|:-------------|
| 1A00 | ['A00.9'] |
| 8A00.0 | ['G20'] |
| BA00.Z | ['I10'] |
Model Information
| Model Name: | icd11_icd10_mapper_202601 |
| Compatibility: | Healthcare NLP 6.4.1+ |
| License: | Licensed |
| Edition: | Official |
| Input Labels: | [ner_chunk] |
| Output Labels: | [mappings] |
| Language: | en |
| Size: | 213.5 KB |