Description
This pretrained pipeline is built on the top of icdo_snomed_mapper model.
Predicted Entities
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("""Put your text here.""")
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 4.4.4+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 137.3 KB |
Included Models
- DocumentAssembler
- TokenizerModel
- ChunkMapperModel