Description
This model maps clinical entities (domain: Conditions) to Snomed codes using sbert_jsl_medium_uncased Sentence Bert Embeddings.
Predicted Entities
Snomed Codes and their normalized definition with sbert_jsl_medium_uncased embeddings.
How to use
documentAssembler = DocumentAssembler()\
.setInputCol("text")\
.setOutputCol("ner_chunk")
sbert_embedder = BertSentenceEmbeddings.pretrained('sbert_jsl_medium_uncased', 'en','clinical/models')\
.setInputCols(["ner_chunk"])\
.setOutputCol("sbert_embeddings")
snomed_resolver = SentenceEntityResolverModel.pretrained("sbertresolve_snomed_conditions", "en", "clinical/models") \
.setInputCols(["sbert_embeddings"]) \
.setOutputCol("snomed_code")\
.setDistanceFunction("EUCLIDEAN")
snomed_pipelineModel = PipelineModel(
stages = [
documentAssembler,
sbert_embedder,
snomed_resolver
])
snomed_lp = LightPipeline(snomed_pipelineModel)
result = snomed_lp.fullAnnotate("schizophrenia")
val documentAssembler = DocumentAssembler()
.setInputCol("text")
.setOutputCol("ner_chunk")
val sbert_embedder = BertSentenceEmbeddings.pretrained('sbert_jsl_medium_uncased', 'en','clinical/models')
.setInputCols("ner_chunk")
.setOutputCol("sbert_embeddings")
val snomed_resolver = SentenceEntityResolverModel.pretrained("sbertresolve_snomed_conditions", "en", "clinical/models") \
.setInputCols(Array("sbert_embeddings")) \
.setOutputCol("snomed_code")\
.setDistanceFunction("EUCLIDEAN")
val snomed_pipelineModel = new PipelineModel().setStages(Array(documentAssembler,sbert_embedder,snomed_resolver))
val snomed_lp = LightPipeline(snomed_pipelineModel)
val result = snomed_lp.fullAnnotate("schizophrenia")
import nlu
nlu.load("en.resolve.snomed_conditions").predict("""Put your text here.""")
Results
| | chunks | code | resolutions | all_codes | all_distances |
|---:|:--------------|:---------|:-------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------|:-----------------------------------------------------|
| 0 | schizophrenia | 58214004 | [schizophrenia, chronic schizophrenia, borderline schizophrenia, schizophrenia, catatonic, subchronic schizophrenia, ...]| [58214004, 83746006, 274952002, 191542003, 191529003, 16990005, ...] | 0.0000, 0.0774, 0.0838, 0.0927, 0.0970, 0.0970, ...] |
Model Information
| Model Name: | sbertresolve_snomed_conditions |
| Compatibility: | Healthcare NLP 3.1.3+ |
| License: | Licensed |
| Edition: | Official |
| Input Labels: | [ner_chunk, sbert_embeddings] |
| Output Labels: | [snomed_code] |
| Language: | en |
| Case sensitive: | false |