Description
This pretrained pipeline is built on the top of bert_token_classifier_drug_development_trials model.
Live Demo Open in Colab Copy S3 URI
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("bert_token_classifier_drug_development_trials_pipeline", "en", "clinical/models")
pipeline.fullAnnotate("In June 2003, the median overall survival with and without topotecan were 4.0 and 3.6 months, respectively. The best complete response ( CR ) , partial response ( PR ) , stable disease and progressive disease were observed in 23, 63, 55 and 33 patients, respectively, with topotecan, and 11, 61, 66 and 32 patients, respectively, without topotecan.")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("bert_token_classifier_drug_development_trials_pipeline", "en", "clinical/models")
pipeline.fullAnnotate("In June 2003, the median overall survival with and without topotecan were 4.0 and 3.6 months, respectively. The best complete response ( CR ) , partial response ( PR ) , stable disease and progressive disease were observed in 23, 63, 55 and 33 patients, respectively, with topotecan, and 11, 61, 66 and 32 patients, respectively, without topotecan.")
import nlu
nlu.load("en.classify.token_bert.druge_developement.pipeline").predict("""In June 2003, the median overall survival with and without topotecan were 4.0 and 3.6 months, respectively. The best complete response ( CR ) , partial response ( PR ) , stable disease and progressive disease were observed in 23, 63, 55 and 33 patients, respectively, with topotecan, and 11, 61, 66 and 32 patients, respectively, without topotecan.""")
Results
| | chunk | entity |
|---:|:------------------|:--------------|
| 0 | median | Duration |
| 1 | overall survival | End_Point |
| 2 | with | Trial_Group |
| 3 | without topotecan | Trial_Group |
| 4 | 4.0 | Value |
| 5 | 3.6 months | Value |
| 6 | 23 | Patient_Count |
| 7 | 63 | Patient_Count |
| 8 | 55 | Patient_Count |
| 9 | 33 patients | Patient_Count |
| 10 | topotecan | Trial_Group |
| 11 | 11 | Patient_Count |
| 12 | 61 | Patient_Count |
| 13 | 66 | Patient_Count |
| 14 | 32 patients | Patient_Count |
| 15 | without topotecan | Trial_Group |
Model Information
| Model Name: | bert_token_classifier_drug_development_trials_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 3.4.1+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 404.7 MB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- MedicalBertForTokenClassifier
- NerConverter