Description
A pipeline with ner_posology. It will only extract medication entities.
Predicted Entities
DOSAGE, DRUG, DURATION, FORM, FREQUENCY, ROUTE, STRENGTH
How to use
pipeline = PretrainedPipeline('recognize_entities_posology', 'en', 'clinical/models')
res = pipeline.fullAnnotate("""A 28-year-old female with a history of gestational diabetes mellitus, used to take metformin 1000 mg two times a day, presented with a one-week history of polyuria , polydipsia , poor appetite , and vomiting .
She was seen by the endocrinology service and discharged on 40 units of insulin glargine at night, 12 units of insulin lispro with meals.
""")
val era_pipeline = new PretrainedPipeline("recognize_entities_posology", "en", "clinical/models")
val result = era_pipeline.fullAnnotate("""A 28-year-old female with a history of gestational diabetes mellitus, used to take metformin 1000 mg two times a day, presented with a one-week history of polyuria , polydipsia , poor appetite , and vomiting .
She was seen by the endocrinology service and discharged on 40 units of insulin glargine at night, 12 units of insulin lispro with meals.
""")(0)
import nlu
nlu.load("en.recognize_entities.posology").predict("""A 28-year-old female with a history of gestational diabetes mellitus, used to take metformin 1000 mg two times a day, presented with a one-week history of polyuria , polydipsia , poor appetite , and vomiting .
She was seen by the endocrinology service and discharged on 40 units of insulin glargine at night, 12 units of insulin lispro with meals.
""")
Results
| | chunk | begin | end | entity |
|---:|:-----------------|--------:|------:|:----------|
| 0 | metformin | 83 | 91 | DRUG |
| 1 | 1000 mg | 93 | 99 | STRENGTH |
| 2 | two times a day | 101 | 115 | FREQUENCY |
| 3 | 40 units | 270 | 277 | DOSAGE |
| 4 | insulin glargine | 282 | 297 | DRUG |
| 5 | at night | 299 | 306 | FREQUENCY |
| 6 | 12 units | 309 | 316 | DOSAGE |
| 7 | insulin lispro | 321 | 334 | DRUG |
| 8 | with meals | 336 | 345 | FREQUENCY |
Model Information
| Model Name: | recognize_entities_posology |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 4.4.4+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 1.7 GB |
Included Models
- DocumentAssembler
- SentenceDetector
- TokenizerModel
- WordEmbeddingsModel
- MedicalNerModel
- NerConverter