Description
This pretrained pipeline is built on the top of rxnorm_umls_mapper model.
Predicted Entities
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.rxnorm.umls.mapping").predict("""Put your text here.""")
Results
| | rxnorm_code | umls_code |
|---:|:-----------------|:--------------------|
| 0 | 1161611 | 315677 | C3215948 | C0984912 |
Model Information
| Model Name: | rxnorm_umls_mapping |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 4.4.4+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 1.9 MB |
Included Models
- DocumentAssembler
- TokenizerModel
- ChunkMapperModel