Description
This pretrained pipeline is built on the top of ner_pharmacology model.
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("ner_pharmacology_pipeline", "es", "clinical/models")
text = '''e 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("ner_pharmacology_pipeline", "es", "clinical/models")
val text = "e 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)
Results
| | ner_chunks | begin | end | ner_label | confidence |
|---:|:----------------|--------:|------:|:--------------|-------------:|
| 0 | creatinkinasa | 31 | 43 | PROTEINAS | 0.9994 |
| 1 | LDH | 53 | 55 | PROTEINAS | 0.9996 |
| 2 | urea | 65 | 68 | NORMALIZABLES | 0.9996 |
| 3 | CA 19.9 | 80 | 86 | PROTEINAS | 0.99835 |
| 4 | vimentina | 138 | 146 | PROTEINAS | 0.9991 |
| 5 | S-100 | 149 | 153 | PROTEINAS | 0.9996 |
| 6 | HMB-45 | 156 | 161 | PROTEINAS | 0.9986 |
| 7 | actina | 165 | 170 | PROTEINAS | 0.9998 |
| 8 | Cisplatino | 219 | 228 | NORMALIZABLES | 0.9999 |
| 9 | Interleukina II | 231 | 245 | PROTEINAS | 0.99955 |
| 10 | Dacarbacina | 248 | 258 | NORMALIZABLES | 0.9996 |
| 11 | Interferon alfa | 262 | 276 | PROTEINAS | 0.99935 |
Model Information
| Model Name: | ner_pharmacology_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 4.3.0+ |
| License: | Licensed |
| Edition: | Official |
| Language: | es |
| Size: | 318.7 MB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- RoBertaEmbeddings
- MedicalNerModel
- NerConverter