Pipeline to Resolve RxNorm Codes

Description

This pretrained pipeline maps entities with their corresponding RxNorm codes. You’ll just feed your text and it will return the corresponding RxNorm codes.

Predicted Entities

DRUG

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Available as Private API Endpoint

Deploy

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How to use

from sparknlp.pretrained import PretrainedPipeline

resolver_pipeline = PretrainedPipeline("rxnorm_resolver_pipeline", "en", "clinical/models")

result = resolver_pipeline.fullAnnotate("""The patient was given Adapin 10 MG, coumadn 5 mg""")

import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline

val resolver_pipeline = new PretrainedPipeline("rxnorm_resolver_pipeline", "en", "clinical/models")

val result = resolver_pipeline.fullAnnotate("""The patient was given Adapin 10 MG, coumadn 5 mg""")

Results

+------------+---------+-----------+
|chunk       |ner_chunk|rxnorm_code|
+------------+---------+-----------+
|Adapin 10 MG|DRUG     |1000049    |
|coumadn 5 mg|DRUG     |200883     |
+------------+---------+-----------+

Model Information

Included Models

• DocumentAssembler
• SentenceDetector
• TokenizerModel
• WordEmbeddingsModel
• MedicalNerModel
• NerConverterInternalModel
• ChunkMapperModel
• ChunkMapperModel
• ChunkMapperFilterer
• Chunk2Doc
• BertSentenceEmbeddings
• SentenceEntityResolverModel
• ResolverMerger