Description
This pretrained pipeline is built on the top of ner_drugprot_clinical model.
How to use
pipeline = PretrainedPipeline("ner_drugprot_clinical_pipeline", "en", "clinical/models")
pipeline.annotate("Anabolic effects of clenbuterol on skeletal muscle are mediated by beta 2-adrenoceptor activation.")
val pipeline = new PretrainedPipeline("ner_drugprot_clinical_pipeline", "en", "clinical/models")
pipeline.annotate("Anabolic effects of clenbuterol on skeletal muscle are mediated by beta 2-adrenoceptor activation.")
import nlu
nlu.load("en.med_ner.clinical_drugprot.pipeline").predict("""Anabolic effects of clenbuterol on skeletal muscle are mediated by beta 2-adrenoceptor activation.""")
Results
+-------------------------------+---------+
|chunk |ner_label|
+-------------------------------+---------+
|clenbuterol |CHEMICAL |
|beta 2-adrenoceptor |GENE |
+-------------------------------+---------+
Model Information
| Model Name: | ner_drugprot_clinical_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 3.4.1+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 1.7 GB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- WordEmbeddingsModel
- MedicalNerModel
- NerConverter