Pipeline to Mapping RxNorm Codes with Corresponding National Drug Codes (NDC)

Description

This pretrained pipeline maps RXNORM codes to NDC codes without using any text data. You’ll just feed white space-delimited RXNORM codes and it will return the corresponding two different types of ndc codes which are called package ndc and product ndc.

Predicted Entities

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How to use

from sparknlp.pretrained import PretrainedPipeline

pipeline = PretrainedPipeline("rxnorm_ndc_mapping", "en", "clinical/models")

result = pipeline.fullAnnotate(1652674 259934)

import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline

val pipeline = new PretrainedPipeline("rxnorm_ndc_mapping", "en", "clinical/models")

val result = pipeline.fullAnnotate(1652674 259934)

import nlu
nlu.load("en.map_entity.rxnorm_to_ndc.pipe").predict("""Put your text here.""")

Results

{'document': ['1652674 259934'],
'package_ndc': ['62135-0625-60', '13349-0010-39'],
'product_ndc': ['46708-0499', '13349-0010'],
'rxnorm_code': ['1652674', '259934']}

Model Information

Included Models

• DocumentAssembler
• TokenizerModel
• ChunkMapperModel
• ChunkMapperModel