Pipeline to Mapping ICD10-CM Codes with Their Corresponding ICD-9-CM Codes

Description

This pretrained pipeline is built on the top of icd10_icd9_mapper model.

Predicted Entities

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Available as Private API Endpoint

Deploy

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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("""Put your text here.""")

Results

|   | icd10cm_code | icd9_code |
|--:|-------------:|----------:|
| 0 |         Z833 |      V180 |
| 1 |        A0100 |      0020 |
| 2 |         A000 |      0010 |

Model Information

Included Models

• DocumentAssembler
• TokenizerModel
• ChunkMapperModel