Description
This pretrained pipeline is built on the top of snomed_icdo_mapper model.
Predicted Entities
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("snomed_icdo_mapping", "en", "clinical/models")
result = pipeline.fullAnnotate(10376009 2026006 26638004)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("snomed_icdo_mapping", "en", "clinical/models")
val result = pipeline.fullAnnotate(10376009 2026006 26638004)
import nlu
nlu.load("en.map_entity.snomed_to_icdo.pipe").predict("""Put your text here.""")
Results
| | snomed_code | icdo_code |
|---:|:------------------------------|:-------------------------|
| 0 | 10376009 | 2026006 | 26638004 | 8050/2 | 9014/0 | 8322/0 |
Model Information
| Model Name: | snomed_icdo_mapping |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 4.4.4+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 212.8 KB |
Included Models
- DocumentAssembler
- TokenizerModel
- ChunkMapperModel