Description
This pretrained model maps ICD10-CM codes to corresponding SNOMED codes under the Unified Medical Language System (UMLS).
Predicted Entities
snomed_code
How to use
documentAssembler = DocumentAssembler()\
.setInputCol("text")\
.setOutputCol("ner_chunk")
sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli", "en", "clinical/models")\
.setInputCols(["ner_chunk"])\
.setOutputCol("sbert_embeddings")
icd_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_icd10cm_augmented_billable_hcc", "en", "clinical/models") \
.setInputCols(["sbert_embeddings"]) \
.setOutputCol("icd10cm_code")\
.setDistanceFunction("EUCLIDEAN")
chunkerMapper = ChunkMapperModel.pretrained("icd10cm_snomed_mapper", "en", "clinical/models")\
.setInputCols(["icd10cm_code"])\
.setOutputCol("mappings")\
.setRels(["snomed_code"])
pipeline = Pipeline(stages = [
documentAssembler,
sbert_embedder,
icd_resolver,
chunkerMapper])
model = pipeline.fit(spark.createDataFrame([[""]]).toDF("text"))
light_pipeline= LightPipeline(model)
result = light_pipeline.fullAnnotate("Diabetes Mellitus")
val documentAssembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("ner_chunk")
val sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli", "en", "clinical/models")
.setInputCols(Array("ner_chunk"))
.setOutputCol("sbert_embeddings")
val icd_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_icd10cm_augmented_billable_hcc", "en", "clinical/models")
.setInputCols(Array("sbert_embeddings"))
.setOutputCol("icd10cm_code")
.setDistanceFunction("EUCLIDEAN")
val chunkerMapper = ChunkMapperModel.pretrained("icd10cm_snomed_mapper", "en","clinical/models")
.setInputCols(Array("icd10cm_code"))
.setOutputCol("mappings")
.setRels(Array("snomed_code"))
val pipeline = new Pipeline(stages = Array(
documentAssembler,
sbert_embedder,
icd_resolver,
chunkerMapper))
val data = Seq("Diabetes Mellitus").toDS.toDF("text")
val result= pipeline.fit(data).transform(data)
import nlu
nlu.load("en.icd10cm_to_snomed").predict("""Diabetes Mellitus""")
Results
| | ner_chunk | icd10cm_code | snomed_mappings |
|---:|:------------------|:---------------|------------------:|
| 0 | Diabetes Mellitus | Z833 | 160402005 |
Model Information
| Model Name: | icd10cm_snomed_mapper |
| Compatibility: | Healthcare NLP 3.5.3+ |
| License: | Licensed |
| Edition: | Official |
| Input Labels: | [icd10_code] |
| Output Labels: | [mappings] |
| Language: | en |
| Size: | 1.1 MB |