Pipeline to Detect Drug Entities - Generic

Description

This pre-trained pipeline is designed to identify generic DRUG entities in clinical texts. It was built on top of the ner_posology_greedy, ner_jsl_greedy, ner_drugs_large and drug_matcher models to detect the entities DRUG, DOSAGE, ROUTE and STRENGTH, chunking them into a larger entity as DRUG when they appear together. The main distinction from the medication_ner_pipeline is that it chunks these entities together, whereas the medication_ner_pipeline chunks them separately.

Predicted entities: DRUG

Predicted Entities

DRUG

Live Demo Open in Colab Download Copy S3 URI

How to use

from sparknlp.pretrained import PretrainedPipeline

ner_pipeline = PretrainedPipeline("ner_medication_generic_pipeline", "en", "clinical/models")

result = ner_pipeline.annotate("""The patient described the epigastric pain as burning and worsening after meals, often accompanied by heartburn and regurgitation, particularly when lying down.
Additionally, he reported discomfort and bloating associated with infrequent bowel movements. In response, his doctor prescribed a regimen tailored to his conditions:
Thiamine 100 mg , Folic acid 1 mg , multivitamins , Calcium carbonate plus Vitamin D 250 mg , Heparin 5000 units subcutaneously , Prilosec 20 mg , Senna two tabs .""")

import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline

val ner_pipeline = PretrainedPipeline("ner_medication_generic_pipeline", "en", "clinical/models")

val result = ner_pipeline.annotate("""The patient described the epigastric pain as burning and worsening after meals, often accompanied by heartburn and regurgitation, particularly when lying down.
Additionally, he reported discomfort and bloating associated with infrequent bowel movements. In response, his doctor prescribed a regimen tailored to his conditions:
Thiamine 100 mg , Folic acid 1 mg , multivitamins , Calcium carbonate plus Vitamin D 250 mg , Heparin 5000 units subcutaneously , Prilosec 20 mg , Senna two tabs .""")

Results

+---------------------------------+---------+
|medication_greedy_chunk          |ner_label|
+---------------------------------+---------+
|Thiamine 100 mg                  |DRUG     |
|Folic acid 1 mg                  |DRUG     |
|multivitamins                    |DRUG     |
|Calcium carbonate                |DRUG     |
|Vitamin D 250 mg                 |DRUG     |
|Heparin 5000 units subcutaneously|DRUG     |
|Prilosec 20 mg                   |DRUG     |
|Senna two tabs                   |DRUG     |
+---------------------------------+---------+

Model Information

Included Models

• DocumentAssembler
• SentenceDetectorDLModel
• TokenizerModel
• WordEmbeddingsModel
• MedicalNerModel
• NerConverterInternalModel
• MedicalNerModel
• NerConverterInternalModel
• MedicalNerModel
• NerConverter
• TextMatcherInternalModel
• ChunkMergeModel