Description
This pretrained model maps entities with their corresponding ICD-9-CM codes.
Important Note: Mappers extract additional information such as extended descriptions and categories related to Concept codes (such as RxNorm, ICD10, CPT, MESH, NDC, UMLS, etc.). They generally take Concept Codes, which are the outputs of EntityResolvers, as input. When creating a pipeline that contains ‘Mapper’, it is necessary to use the ChunkMapperModel after an EntityResolverModel.
Predicted Entities
icd9_code
How to use
document_assembler = DocumentAssembler()\
.setInputCol('text')\
.setOutputCol('doc')
chunk_assembler = Doc2Chunk()\
.setInputCols(['doc'])\
.setOutputCol('ner_chunk')
chunkerMapper = ChunkMapperModel\
.pretrained("icd9_mapper", "en", "clinical/models")\
.setInputCols(["ner_chunk"])\
.setOutputCol("mappings")\
.setRels(["icd9_code"])
mapper_pipeline = Pipeline(stages=[
document_assembler,
chunk_assembler,
chunkerMapper
])
test_data = spark.createDataFrame([["24 completed weeks of gestation"]]).toDF("text")
result = mapper_pipeline.fit(test_data).transform(test_data)
val document_assembler = DocumentAssembler()
.setInputCol("text")
.setOutputCol("doc")
val chunk_assembler = Doc2Chunk()
.setInputCols(Array("doc"))
.setOutputCol("ner_chunk")
val chunkerMapper = ChunkMapperModel
.pretrained("icd9_mapper", "en", "clinical/models")
.setInputCols(Array("ner_chunk"))
.setOutputCol("mappings")
.setRels(Array("icd9_code"))
val mapper_pipeline = new Pipeline().setStages(Array(
document_assembler,
chunk_assembler,
chunkerMapper))
val test_data = Seq("24 completed weeks of gestation").toDS.toDF("text")
val result = mapper_pipeline.fit(test_data).transform(test_data)
import nlu
nlu.load("en.map_entity.icd9").predict("""24 completed weeks of gestation""")
Results
+-------------------------------+------------+
|chunk |icd9_mapping|
+-------------------------------+------------+
|24 completed weeks of gestation|765.22 |
+-------------------------------+------------+
Model Information
| Model Name: | icd9_mapper |
| Compatibility: | Healthcare NLP 4.1.0+ |
| License: | Licensed |
| Edition: | Official |
| Input Labels: | [ner_chunk] |
| Output Labels: | [mappings] |
| Language: | en |
| Size: | 374.4 KB |