Description
This pretrained pipeline is built on the top of rxnorm_umls_mapper model.
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("rxnorm_umls_mapping", "en", "clinical/models")
result= pipeline.fullAnnotate("1161611 315677")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("rxnorm_umls_mapping", "en", "clinical/models")
val result= pipeline.fullAnnotate("1161611 315677")
import nlu
nlu.load("en.resolve.rxnorm.umls").predict("""1161611 315677""")
Results
| | rxnorm_code | umls_code |
|---:|:-----------------|:--------------------|
| 0 | 1161611 | 315677 | C3215948 | C0984912 |
Model Information
| Model Name: | rxnorm_umls_mapping |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 3.5.3+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 1.9 MB |
Included Models
- DocumentAssembler
- TokenizerModel
- ChunkMapperModel