Description
This pipeline is designed to extract medication entities from texts.
2 NER models and a text matcher are used to extract the medication entities.
How to use
from sparknlp.pretrained import PretrainedPipeline
ner_pipeline = PretrainedPipeline("explain_clinical_doc_medication_light", "en", "clinical/models")
result = ner_pipeline.annotate("""John Smith, a 55-year-old male with a medical history of hypertension, Type 2 Diabetes Mellitus, Hyperlipidemia, Gastroesophageal Reflux Disease (GERD),
and chronic constipation, presented with persistent epigastric pain, heartburn, and infrequent bowel movements.
He described the epigastric pain as burning and worsening after meals, often accompanied by heartburn and regurgitation, particularly when lying down.
In response, his doctor prescribed a regimen tailored to his conditions:
Thiamine 100 mg q.day , Folic acid 1 mg q.day , multivitamins q.day , Calcium carbonate plus Vitamin D 250 mg t.i.d. , Heparin 5000 units subcutaneously b.i.d. , Prilosec 20 mg q.day , Senna two tabs qhs.
""")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val ner_pipeline = PretrainedPipeline("explain_clinical_doc_medication_light", "en", "clinical/models")
val result = ner_pipeline.annotate("""John Smith, a 55-year-old male with a medical history of hypertension, Type 2 Diabetes Mellitus, Hyperlipidemia, Gastroesophageal Reflux Disease (GERD),
and chronic constipation, presented with persistent epigastric pain, heartburn, and infrequent bowel movements.
He described the epigastric pain as burning and worsening after meals, often accompanied by heartburn and regurgitation, particularly when lying down.
In response, his doctor prescribed a regimen tailored to his conditions:
Thiamine 100 mg q.day , Folic acid 1 mg q.day , multivitamins q.day , Calcium carbonate plus Vitamin D 250 mg t.i.d. , Heparin 5000 units subcutaneously b.i.d. , Prilosec 20 mg q.day , Senna two tabs qhs.
""")
Results
| | chunks | begin | end | entities |
|---:|:------------------|--------:|------:|:-----------|
| 0 | Thiamine | 493 | 500 | DRUG |
| 1 | 100 mg | 502 | 507 | STRENGTH |
| 2 | q.day | 509 | 513 | FREQUENCY |
| 3 | Folic acid | 517 | 526 | DRUG |
| 4 | 1 mg | 528 | 531 | STRENGTH |
| 5 | q.day | 533 | 537 | FREQUENCY |
| 6 | multivitamins | 541 | 553 | DRUG |
| 7 | q.day | 555 | 559 | FREQUENCY |
| 8 | Calcium carbonate | 563 | 579 | DRUG |
| 9 | Vitamin D | 586 | 594 | DRUG |
| 10 | 250 mg | 596 | 601 | STRENGTH |
| 11 | t.i.d | 603 | 607 | FREQUENCY |
| 12 | Heparin | 612 | 618 | DRUG |
| 13 | 5000 units | 620 | 629 | DOSAGE |
| 14 | subcutaneously | 631 | 644 | ROUTE |
| 15 | b.i.d | 646 | 650 | FREQUENCY |
| 16 | Prilosec | 655 | 662 | DRUG |
| 17 | 20 mg | 664 | 668 | STRENGTH |
| 18 | q.day | 670 | 674 | FREQUENCY |
| 19 | Senna | 678 | 682 | DRUG |
| 20 | two | 684 | 686 | DOSAGE |
| 21 | tabs | 688 | 691 | FORM |
| 22 | qhs | 693 | 695 | FREQUENCY |
Model Information
| Model Name: | explain_clinical_doc_medication_light |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 6.0.2+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 1.7 GB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- WordEmbeddingsModel
- MedicalNerModel
- NerConverterInternalModel
- MedicalNerModel
- NerConverterInternalModel
- TextMatcherInternalModel
- ChunkMergeModel