Description
This pretrained pipeline is built on the top of icdo_snomed_mapper model.
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline= PretrainedPipeline("icdo_snomed_mapping", "en", "clinical/models")
result= pipeline.fullAnnotate("8120/1 8170/3 8380/3")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline= new PretrainedPipeline("icdo_snomed_mapping", "en", "clinical/models")
val result= pipeline.fullAnnotate("8120/1 8170/3 8380/3")
import nlu
nlu.load("en.map_entity.icdo_to_snomed.pipe").predict("""8120/1 8170/3 8380/3""")
Results
| | icdo_code | snomed_code |
|---:|:-------------------------|:-------------------------------|
| 0 | 8120/1 | 8170/3 | 8380/3 | 45083001 | 25370001 | 30289006 |
Model Information
| Model Name: | icdo_snomed_mapping |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 3.5.3+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 133.2 KB |
Included Models
- DocumentAssembler
- TokenizerModel
- ChunkMapperModel