Description
This pretrained model maps ICD-10-CM codes, subsequently providing corresponding causes and generating claim analysis codes for each respective ICD-10-CM code. If there is no equivalent claim analysis code, the result will be None.
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
icd10cm_cause, icd10cm_claim_analysis_code
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How to use
document_assembler = DocumentAssembler()\
.setInputCol("text")\
.setOutputCol("document")
chunk_assembler = Doc2Chunk()\
.setInputCols("document")\
.setOutputCol("icd_chunk")
chunkerMapper = ChunkMapperModel.pretrained("icd10cm_cause_claim_mapper", "en", "clinical/models")\
.setInputCols(["icd_chunk"])\
.setOutputCol("mappings")\
.setRels(["icd10cm_cause", "icd10cm_claim_analysis_code"])
pipeline = Pipeline().setStages([document_assembler,
chunk_assembler,
chunkerMapper])
model = pipeline.fit(spark.createDataFrame([['']]).toDF('text'))
lp = LightPipeline(model)
res = lp.fullAnnotate(["D69.51", "G43.83", "A18.03"])
val document_assembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")
val chunk_assembler = new Doc2Chunk()
.setInputCols("document")
.setOutputCol("icd_chunk")
val chunkerMapper = ChunkMapperModel.pretrained("icd10cm_cause_claim_mapper", "en", "clinical/models")
.setInputCols(Array("icd_chunk"))
.setOutputCol("mappings")
.setRels(Array("icd10cm_cause", "icd10cm_claim_analysis_code"))
val mapper_pipeline = new Pipeline().setStages(Array(document_assembler, chunk_assembler, chunkerMapper))
val data = Seq(Array("D69.51", "G43.83", "A18.03")).toDS.toDF("text")
val result = pipeline.fit(data).transform(data)
Results
+------------+------------------------------------+---------------------------+
|icd10cm_code|cause |icd10cm_claim_analysis_code|
+------------+------------------------------------+---------------------------+
|D69.51 |Unintentional injuries |D69.51 |
|D69.51 |Adverse effects of medical treatment|D69.51 |
|G43.83 |Headache disorders |G43.83 |
|G43.83 |Tension-type headache |G43.83 |
|G43.83 |Migraine |G43.83 |
|A18.03 |Whooping cough |A18.03 |
+------------+------------------------------------+---------------------------+
Model Information
| Model Name: | icd10cm_cause_claim_mapper |
| Compatibility: | Healthcare NLP 4.4.0+ |
| License: | Licensed |
| Edition: | Official |
| Input Labels: | [ner_chunk] |
| Output Labels: | [mappings] |
| Language: | en |
| Size: | 600.2 KB |