Description
This pretrained pipeline is built on the top of ner_diseases_biobert model.
Predicted Entities
Disease
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("ner_diseases_biobert_pipeline", "en", "clinical/models")
text = '''Indomethacin resulted in histopathologic findings typical of interstitial cystitis, such as leaky bladder epithelium and mucosal mastocytosis. The true incidence of nonsteroidal anti-inflammatory drug-induced cystitis in humans must be clarified by prospective clinical trials. An open-label phase II study of low-dose thalidomide in androgen-independent prostate cancer.'''
result = pipeline.fullAnnotate(text)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("ner_diseases_biobert_pipeline", "en", "clinical/models")
val text = "Indomethacin resulted in histopathologic findings typical of interstitial cystitis, such as leaky bladder epithelium and mucosal mastocytosis. The true incidence of nonsteroidal anti-inflammatory drug-induced cystitis in humans must be clarified by prospective clinical trials. An open-label phase II study of low-dose thalidomide in androgen-independent prostate cancer."
val result = pipeline.fullAnnotate(text)
import nlu
nlu.load("en.med_ner.diseases_biobert.pipeline").predict("""Indomethacin resulted in histopathologic findings typical of interstitial cystitis, such as leaky bladder epithelium and mucosal mastocytosis. The true incidence of nonsteroidal anti-inflammatory drug-induced cystitis in humans must be clarified by prospective clinical trials. An open-label phase II study of low-dose thalidomide in androgen-independent prostate cancer.""")
Results
| | ner_chunk | begin | end | ner_label | confidence |
|---:|:----------------------|--------:|------:|:------------|-------------:|
| 0 | interstitial cystitis | 61 | 81 | Disease | 0.99655 |
| 1 | mastocytosis | 129 | 140 | Disease | 0.8569 |
| 2 | cystitis | 209 | 216 | Disease | 0.9717 |
| 3 | prostate cancer | 355 | 369 | Disease | 0.85965 |
Model Information
| Model Name: | ner_diseases_biobert_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 4.4.4+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 422.1 MB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- BertEmbeddings
- MedicalNerModel
- NerConverter