Description
This pretrained pipeline is built on the top of ner_sdoh_mentions model.
Predicted Entities
behavior_alcohol, behavior_drug, sdoh_education, behavior_tobacco, sdoh_economics, sdoh_environment, sdoh_community
Live Demo Open in Colab Copy S3 URI
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("ner_sdoh_mentions_pipeline", "en", "clinical/models")
text = '''Mr. Known lastname 9880 is a pleasant, cooperative gentleman with a long standing history (20 years) diverticulitis. He is married and has 3 children. He works in a bank. He denies any alcohol or intravenous drug use. He has been smoking for many years.'''
result = pipeline.fullAnnotate(text)
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("ner_sdoh_mentions_pipeline", "en", "clinical/models")
val text = "Mr. Known lastname 9880 is a pleasant, cooperative gentleman with a long standing history (20 years) diverticulitis. He is married and has 3 children. He works in a bank. He denies any alcohol or intravenous drug use. He has been smoking for many years."
val result = pipeline.fullAnnotate(text)
Results
| | chunks | begin | end | entities | confidence |
|---:|:-----------------|--------:|------:|:-----------------|-------------:|
| 0 | married | 123 | 129 | sdoh_community | 0.9972 |
| 1 | children | 141 | 148 | sdoh_community | 0.9999 |
| 2 | works | 154 | 158 | sdoh_economics | 0.9995 |
| 3 | alcohol | 185 | 191 | behavior_alcohol | 0.9925 |
| 4 | intravenous drug | 196 | 211 | behavior_drug | 0.9803 |
| 5 | smoking | 230 | 236 | behavior_tobacco | 0.9997 |
Model Information
| Model Name: | ner_sdoh_mentions_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 4.3.0+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 1.7 GB |
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- TokenizerModel
- WordEmbeddingsModel
- MedicalNerModel
- NerConverterInternalModel