Description
This pretrained pipeline is built on the top of ner_clinical_trials_abstracts model.
Predicted Entities
Age, AllocationRatio, Author, BioAndMedicalUnit, CTAnalysisApproach, CTDesign, Confidence, Country, DisorderOrSyndrome, DoseValue, Drug, DrugTime, Duration, Journal, NumberPatients, PMID, PValue, PercentagePatients, PublicationYear, TimePoint, Value
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("ner_clinical_trials_abstracts_pipeline", "en", "clinical/models")
text = '''A one-year, randomised, multicentre trial comparing insulin glargine with NPH insulin in combination with oral agents in patients with type 2 diabetes. In a multicentre, open, randomised study, 570 patients with Type 2 diabetes, aged 34 - 80 years, were treated for 52 weeks with insulin glargine or NPH insulin given once daily at bedtime.'''
result = pipeline.fullAnnotate(text)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("ner_clinical_trials_abstracts_pipeline", "en", "clinical/models")
val text = "A one-year, randomised, multicentre trial comparing insulin glargine with NPH insulin in combination with oral agents in patients with type 2 diabetes. In a multicentre, open, randomised study, 570 patients with Type 2 diabetes, aged 34 - 80 years, were treated for 52 weeks with insulin glargine or NPH insulin given once daily at bedtime."
val result = pipeline.fullAnnotate(text)
import nlu
nlu.load("en.med_ner.clinical_trials_abstracts.pipe").predict("""A one-year, randomised, multicentre trial comparing insulin glargine with NPH insulin in combination with oral agents in patients with type 2 diabetes. In a multicentre, open, randomised study, 570 patients with Type 2 diabetes, aged 34 - 80 years, were treated for 52 weeks with insulin glargine or NPH insulin given once daily at bedtime.""")
Results
| | ner_chunks | begin | end | ner_label | confidence |
|---:|:-----------------|--------:|------:|:-------------------|-------------:|
| 0 | randomised | 12 | 21 | CTDesign | 0.9996 |
| 1 | multicentre | 24 | 34 | CTDesign | 0.9998 |
| 2 | insulin glargine | 52 | 67 | Drug | 0.99135 |
| 3 | NPH insulin | 74 | 84 | Drug | 0.9687 |
| 4 | type 2 diabetes | 135 | 149 | DisorderOrSyndrome | 0.999933 |
| 5 | multicentre | 157 | 167 | CTDesign | 0.9997 |
| 6 | open | 170 | 173 | CTDesign | 0.9988 |
| 7 | randomised | 176 | 185 | CTDesign | 0.9984 |
| 8 | 570 | 194 | 196 | NumberPatients | 0.9906 |
| 9 | Type 2 diabetes | 212 | 226 | DisorderOrSyndrome | 0.9999 |
| 10 | 34 | 234 | 235 | Age | 0.9999 |
| 11 | 80 | 239 | 240 | Age | 0.9931 |
| 12 | 52 weeks | 266 | 273 | Duration | 0.9794 |
| 13 | insulin glargine | 280 | 295 | Drug | 0.989 |
| 14 | NPH insulin | 300 | 310 | Drug | 0.97955 |
| 15 | once daily | 318 | 327 | DrugTime | 0.999 |
| 16 | bedtime | 332 | 338 | DrugTime | 0.9937 |
Model Information
| Model Name: | ner_clinical_trials_abstracts_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 4.3.0+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 1.7 GB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- WordEmbeddingsModel
- MedicalNerModel
- NerConverterInternalModel