Description
This pretrained pipeline is built on the top of ner_ade_clinicalbert model.
Predicted Entities
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("ner_ade_clinicalbert_pipeline", "en", "clinical/models")
text = '''Been taking Lipitor for 15 years , have experienced severe fatigue a lot!!! . Doctor moved me to voltaren 2 months ago , so far , have only experienced cramps.'''
result = pipeline.fullAnnotate(text)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("ner_ade_clinicalbert_pipeline", "en", "clinical/models")
val text = "Been taking Lipitor for 15 years , have experienced severe fatigue a lot!!! . Doctor moved me to voltaren 2 months ago , so far , have only experienced cramps."
val result = pipeline.fullAnnotate(text)
import nlu
nlu.load("en.med_ner.clinical_bert_ade.pipeline").predict("""Been taking Lipitor for 15 years , have experienced severe fatigue a lot!!! . Doctor moved me to voltaren 2 months ago , so far , have only experienced cramps.""")
Results
| | ner_chunks | begin | end | ner_label | confidence |
|---:|:---------------|--------:|------:|:------------|-------------:|
| 0 | Lipitor | 12 | 18 | DRUG | 0.9975 |
| 1 | severe fatigue | 52 | 65 | ADE | 0.7094 |
| 2 | voltaren | 97 | 104 | DRUG | 0.9202 |
| 3 | cramps | 152 | 157 | ADE | 0.5992 |
Model Information
| Model Name: | ner_ade_clinicalbert_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 4.4.4+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 422.3 MB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- BertEmbeddings
- MedicalNerModel
- NerConverterInternalModel