Description
This pretrained pipeline is built on the top of bert_token_classifier_pharmacology model.
Predicted Entities
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("bert_token_classifier_pharmacology_pipeline", "es", "clinical/models")
text = '''Se realiza analítica destacando creatinkinasa 736 UI, LDH 545 UI, urea 63 mg/dl, CA 19.9 64,1 U/ml. Inmunofenotípicamente el tumor expresó vimentina, S-100, HMB-45 y actina. Se instauró el tratamiento con quimioterapia (Cisplatino, Interleukina II, Dacarbacina e Interferon alfa).'''
result = pipeline.fullAnnotate(text)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("bert_token_classifier_pharmacology_pipeline", "es", "clinical/models")
val text = "Se realiza analítica destacando creatinkinasa 736 UI, LDH 545 UI, urea 63 mg/dl, CA 19.9 64,1 U/ml. Inmunofenotípicamente el tumor expresó vimentina, S-100, HMB-45 y actina. Se instauró el tratamiento con quimioterapia (Cisplatino, Interleukina II, Dacarbacina e Interferon alfa)."
val result = pipeline.fullAnnotate(text)
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("bert_token_classifier_pharmacology_pipeline", "es", "clinical/models")
text = '''Se realiza analítica destacando creatinkinasa 736 UI, LDH 545 UI, urea 63 mg/dl, CA 19.9 64,1 U/ml. Inmunofenotípicamente el tumor expresó vimentina, S-100, HMB-45 y actina. Se instauró el tratamiento con quimioterapia (Cisplatino, Interleukina II, Dacarbacina e Interferon alfa).'''
result = pipeline.fullAnnotate(text)
Results
| | ner_chunk | begin | end | ner_label | confidence |
|---:|:----------------|--------:|------:|:--------------|-------------:|
| 0 | creatinkinasa | 32 | 44 | PROTEINAS | 0.999973 |
| 1 | LDH | 54 | 56 | PROTEINAS | 0.999972 |
| 2 | urea | 66 | 69 | NORMALIZABLES | 0.999977 |
| 3 | CA 19.9 | 81 | 87 | PROTEINAS | 0.999964 |
| 4 | vimentina | 139 | 147 | PROTEINAS | 0.999961 |
| 5 | S-100 | 150 | 154 | PROTEINAS | 0.999861 |
| 6 | HMB-45 | 157 | 162 | PROTEINAS | 0.999965 |
| 7 | actina | 166 | 171 | PROTEINAS | 0.999967 |
| 8 | Cisplatino | 220 | 229 | NORMALIZABLES | 0.999988 |
| 9 | Interleukina II | 232 | 246 | PROTEINAS | 0.999965 |
| 10 | Dacarbacina | 249 | 259 | NORMALIZABLES | 0.999988 |
| 11 | Interferon alfa | 263 | 277 | PROTEINAS | 0.999961 |
Model Information
| Model Name: | bert_token_classifier_pharmacology_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 4.4.4+ |
| License: | Licensed |
| Edition: | Official |
| Language: | es |
| Size: | 410.6 MB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- MedicalBertForTokenClassifier
- NerConverterInternalModel