Description
This pretrained pipeline maps SNOMED codes to their corresponding ICD-10, ICD-O, and UMLS codes. You’ll just feed white space-delimited SNOMED codes and get the result.
How to use
from sparknlp.pretrained import PretrainedPipeline
snomed_pipeline = PretrainedPipeline("snomed_multi_mapper_pipeline", "en", "clinical/models")
result = snomed_pipeline.fullAnnotate("""10000006 128501000""")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val snomed_pipeline = new PretrainedPipeline("snomed_multi_mapper_pipeline", "en", "clinical/models")
val result = snomed_pipeline.fullAnnotate("""10000006 128501000""")
Results
| | snomed_code | icd10_mappings | icdo_mappings | umls_mappings |
|---:|--------------:|:-----------------|:----------------|:----------------|
| 0 | 10000006 | R07.9 | NONE | C0232289 |
| 1 | 128501000 | NONE | C49.5 | C0448606 |
Model Information
| Model Name: | snomed_multi_mapper_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 5.0.1+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 6.8 MB |
Included Models
- DocumentAssembler
- TokenizerModel
- ChunkMapperModel
- ChunkMapperModel
- ChunkMapperModel