Description
This pretrained pipeline is built on the top of icd10_icd9_mapper model.
Predicted Entities
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline= PretrainedPipeline("icd10_icd9_mapping", "en", "clinical/models")
result= pipeline.fullAnnotate('Z833 A0100 A000')
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline= new PretrainedPipeline("icd10_icd9_mapping", "en", "clinical/models")
val result= pipeline.fullAnnotate('Z833 A0100 A000')
import nlu
nlu.load("en.icd10_icd9.mapping").predict("""Z833 A0100 A000""")
Results
| | icd10_code | icd9_code |
|---:|:--------------------|:-------------------|
| 0 | Z833 | A0100 | A000 | V180 | 0020 | 0010 |
Model Information
| Model Name: | icd10_icd9_mapping |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 4.1.0+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 589.5 KB |
Included Models
- DocumentAssembler
- TokenizerModel
- ChunkMapperModel