Description
A pretrained resolver pipeline to extract medications and resolve their adverse reactions (ADE), RxNorm, UMLS, NDC, SNOMED CT codes, and action/treatments in clinical text.
Action/treatments are available for branded medication, and SNOMED codes are available for non-branded medication.
This pipeline can be used with Spark transform. You can use medication_resolver_pipeline as Lightpipeline (with annotate/fullAnnotate).
How to use
from sparknlp.pretrained import PretrainedPipeline
medication_resolver_pipeline = PretrainedPipeline("medication_resolver_transform_pipeline", "en", "clinical/models")
text = """The patient was prescribed Amlodopine Vallarta 10-320mg, Eviplera. The other patient is given Lescol 40 MG and Everolimus 1.5 mg tablet."""
data = spark.createDataFrame([[text]]).toDF("text")
result = medication_resolver_pipeline.transform(data)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val medication_resolver_pipeline = new PretrainedPipeline("medication_resolver_transform_pipeline", "en", "clinical/models")
val data = Seq("""The patient was prescribed Amlodopine Vallarta 10-320mg, Eviplera. The other patient is given Lescol 40 MG and Everolimus 1.5 mg tablet.""").toDS.toDF("text")
val result = medication_resolver_pipeline.fit(data).transform(data)
import nlu
nlu.load("en.resolve.medication_transform.pipeline").predict("""The patient was prescribed Amlodopine Vallarta 10-320mg, Eviplera. The other patient is given Lescol 40 MG and Everolimus 1.5 mg tablet.""")
Results
| chunk | ner_label | ADE | RxNorm | Action | Treatment | UMLS | SNOMED_CT | NDC_Product | NDC_Package |
|:-----------------------------|:------------|:----------------------------|---------:|:---------------------------|:-------------------------------------------|:---------|:------------|:--------------|:--------------|
| Amlodopine Vallarta 10-320mg | DRUG | Gynaecomastia | 722131 | NONE | NONE | C1949334 | 425838008 | 00093-7693 | 00093-7693-56 |
| Eviplera | DRUG | Anxiety | 217010 | Inhibitory Bone Resorption | Osteoporosis | C0720318 | NONE | NONE | NONE |
| Lescol 40 MG | DRUG | NONE | 103919 | Hypocholesterolemic | Heterozygous Familial Hypercholesterolemia | C0353573 | NONE | 00078-0234 | 00078-0234-05 |
| Everolimus 1.5 mg tablet | DRUG | Acute myocardial infarction | 2056895 | NONE | NONE | C4723581 | NONE | 00054-0604 | 00054-0604-21 |
Model Information
| Model Name: | medication_resolver_transform_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 4.3.2+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 3.2 GB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- WordEmbeddingsModel
- MedicalNerModel
- NerConverterInternalModel
- TextMatcherModel
- ChunkMergeModel
- ChunkMapperModel
- ChunkMapperModel
- ChunkMapperFilterer
- Chunk2Doc
- BertSentenceEmbeddings
- SentenceEntityResolverModel
- ResolverMerger
- Doc2Chunk
- ResolverMerger
- ChunkMapperModel
- ChunkMapperModel
- ChunkMapperModel
- Doc2Chunk
- ChunkMapperModel
- ChunkMapperModel
- ChunkMapperModel
- Finisher