Description
This pretrained pipeline maps entities with their corresponding RxNorm codes. You’ll just feed your text and it will return the corresponding RxNorm codes.
Available as Private API Endpoint
How to use
from sparknlp.pretrained import PretrainedPipeline
resolver_pipeline = PretrainedPipeline("rxnorm_resolver_pipeline", "en", "clinical/models")
result = resolver_pipeline.fullAnnotate("""The patient was given Adapin 10 MG, coumadn 5 mg""")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val resolver_pipeline = new PretrainedPipeline("rxnorm_resolver_pipeline", "en", "clinical/models")
val result = resolver_pipeline.fullAnnotate("""The patient was given Adapin 10 MG, coumadn 5 mg""")
Results
+------------+---------+-----------+
|chunk |ner_chunk|rxnorm_code|
+------------+---------+-----------+
|Adapin 10 MG|DRUG |1000049 |
|coumadn 5 mg|DRUG |200883 |
+------------+---------+-----------+
Model Information
| Model Name: | rxnorm_resolver_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 5.0.1+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 3.1 GB |
Included Models
- DocumentAssembler
- SentenceDetector
- TokenizerModel
- WordEmbeddingsModel
- MedicalNerModel
- NerConverterInternalModel
- ChunkMapperModel
- ChunkMapperModel
- ChunkMapperFilterer
- Chunk2Doc
- BertSentenceEmbeddings
- SentenceEntityResolverModel
- ResolverMerger