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).
Predicated Entities
RxNorm Code UMLS Code NDC Code SNOMED CT codes
Predicted Entities
DRUG
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)
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 5.4.1+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 3.3 GB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- WordEmbeddingsModel
- MedicalNerModel
- NerConverterInternalModel
- TextMatcherInternalModel
- ChunkMergeModel
- ChunkMapperModel
- ChunkMapperModel
- ChunkMapperFilterer
- Chunk2Doc
- BertSentenceEmbeddings
- SentenceEntityResolverModel
- ResolverMerger
- Doc2Chunk
- ChunkMapperModel
- ChunkMapperModel
- ChunkMapperModel
- ChunkMapperModel
- ChunkMapperModel
- Doc2Chunk
- ChunkMapperModel
- Finisher