Description
This pretrained pipeline maps RxNorm codes to their corresponding drug brand names, rxnorm extension brand names, action mappings, treatment mappings, UMLS codes, NDC product codes and NDC package codes. You’ll just feed white space-delimited RxNorm codes and get the result.
How to use
from sparknlp.pretrained import PretrainedPipeline
rxnorm_pipeline = PretrainedPipeline("rxnorm_multi_mapper_pipeline", "en", "clinical/models")
result = rxnorm_pipeline.fullAnnotate("""6809 153010 103971""")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val rxnorm_pipeline = new PretrainedPipeline("rxnorm_multi_mapper_pipeline", "en", "clinical/models")
val result = rxnorm_pipeline.fullAnnotate("""6809 153010 103971""")
Results
+-----------+--------------------------------------------------+--------------------------------------------------+---------------+------------------+-------------+--------------------+--------------------+
|rxnorm_code| brandname_mappings| extension_mappings|action_mappings|treatment_mappings|umls_mappings|ndc_product_mappings|ndc_package_mappings|
+-----------+--------------------------------------------------+--------------------------------------------------+---------------+------------------+-------------+--------------------+--------------------+
| 6809|Actoplus Met (metformin):::Avandamet (metformin...|A FORMIN (metformin):::ABERIN MAX (metformin)::...| NONE| NONE| C0025598| 38779-2126| 38779-2126-04|
| 153010| Advil (Advil)| NONE| Analgesic| Period Pain| C0593507| NONE| NONE|
| 103971|Zydol (tramadol hydrochloride 50 MG Oral Capsul...| NONE| Analgesic| Pain| C0353664| NONE| NONE|
+-----------+--------------------------------------------------+--------------------------------------------------+---------------+------------------+-------------+--------------------+--------------------+
Model Information
| Model Name: | rxnorm_multi_mapper_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 5.0.1+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 56.2 MB |
Included Models
- DocumentAssembler
- TokenizerModel
- ChunkMapperModel
- ChunkMapperModel
- ChunkMapperModel
- ChunkMapperModel
- ChunkMapperModel
- ChunkMapperModel
- ChunkMapperModel