Description
This pipeline, extracts medical device entities in clinical text. It recognizes devices including ventilator, defibrillator, stent, insulin pump, glucometer, nebulizer, and more.
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("medical_device_matcher_pipeline", "en", "clinical/models")
sample_text = """ The patient was placed on a ventilator for respiratory support. A pacemaker was implanted to regulate heart rhythm. Blood glucose levels were monitored using a glucometer, and insulin was delivered via an insulin pump."""
result = pipeline.transform(spark.createDataFrame([[sample_text]]).toDF("text"))
from johnsnowlabs import nlp, medical
pipeline = nlp.PretrainedPipeline("medical_device_matcher_pipeline", "en", "clinical/models")
sample_text = """ The patient was placed on a ventilator for respiratory support. A pacemaker was implanted to regulate heart rhythm. Blood glucose levels were monitored using a glucometer, and insulin was delivered via an insulin pump."""
result = pipeline.transform(spark.createDataFrame([[sample_text]]).toDF("text"))
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = PretrainedPipeline("medical_device_matcher_pipeline", "en", "clinical/models")
val sample_text = """ The patient was placed on a ventilator for respiratory support. A pacemaker was implanted to regulate heart rhythm. Blood glucose levels were monitored using a glucometer, and insulin was delivered via an insulin pump."""
val result = pipeline.transform(spark.createDataFrame([[sample_text]]).toDF("text"))
Results
| chunk | begin | end | label |
| :----------- | ----: | --: | :------------- |
| ventilator | 28 | 37 | MEDICAL_DEVICE |
| pacemaker | 66 | 74 | MEDICAL_DEVICE |
| glucometer | 160 | 169 | MEDICAL_DEVICE |
| insulin pump | 205 | 216 | MEDICAL_DEVICE |
Model Information
| Model Name: | medical_device_matcher_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 6.3.0+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 944.5 KB |
Included Models
- DocumentAssembler
- SentenceDetector
- TokenizerModel
- TextMatcherInternalModel
- ChunkConverter