Description
A pipeline with ner_clinical, assertion_dl, re_clinical and ner_posology. It will extract clinical and medication entities, assign assertion status and find relationships between clinical entities.
Predicted Entities
DOSAGE, DRUG, DURATION, FORM, FREQUENCY, PROBLEM, ROUTE, STRENGTH, TEST, TREATMENT
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("explain_clinical_doc_carp", "en", "clinical/models")
text = """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."""
result = pipeline.fullAnnotate(text)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("explain_clinical_doc_carp", "en", "clinical/models")
val text = """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 result = pipeline.fullAnnotate(text)
import nlu
nlu.load("en.explain_doc.carp").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
| | chunks | ner_clinical | assertion | posology_chunk | ner_posology | relations |
|---|-------------------------------|--------------|-----------|------------------|--------------|-----------|
| 0 | gestational diabetes mellitus | PROBLEM | present | metformin | Drug | TrAP |
| 1 | metformin | TREATMENT | present | 1000 mg | Strength | TrCP |
| 2 | polyuria | PROBLEM | present | two times a day | Frequency | TrCP |
| 3 | polydipsia | PROBLEM | present | 40 units | Dosage | TrWP |
| 4 | poor appetite | PROBLEM | present | insulin glargine | Drug | TrCP |
| 5 | vomiting | PROBLEM | present | at night | Frequency | TrAP |
| 6 | insulin glargine | TREATMENT | present | 12 units | Dosage | TrAP |
Model Information
| Model Name: | explain_clinical_doc_carp |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 4.3.0+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 1.8 GB |
Included Models
- DocumentAssembler
- SentenceDetector
- TokenizerModel
- PerceptronModel
- DependencyParserModel
- WordEmbeddingsModel
- MedicalNerModel
- NerConverterInternalModel
- MedicalNerModel
- NerConverterInternalModel
- AssertionDLModel
- RelationExtractionModel