Sound Medical Classification Pipeline - Voice of the Patient

Description

This pretrained pipeline includes the Medical Bert for Sequence Classification model to identify whether the suggestion that is mentioned in the text is medically sound. The pipeline is built on the top of bert_sequence_classifier_vop_sound_medical model.

Predicted Entities

Live Demo Open in Colab Copy S3 URI

How to use

from sparknlp.pretrained import PretrainedPipeline

pipeline = PretrainedPipeline("bert_sequence_classifier_vop_sound_medical_pipeline", "en", "clinical/models")

pipeline.annotate("I had a lung surgery for emphyema and after surgery my xray showing some recovery.")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline

val pipeline = new PretrainedPipeline("bert_sequence_classifier_vop_sound_medical_pipeline", "en", "clinical/models")

val result = pipeline.annotate(I had a lung surgery for emphyema and after surgery my xray showing some recovery.)

Results

| text                                                                               | prediction   |
|:-----------------------------------------------------------------------------------|:-------------|
| I had a lung surgery for emphyema and after surgery my xray showing some recovery. | True         |

Model Information

Model Name: bert_sequence_classifier_vop_sound_medical_pipeline
Type: pipeline
Compatibility: Healthcare NLP 4.4.4+
License: Licensed
Edition: Official
Language: en
Size: 406.4 MB

Included Models

  • DocumentAssembler
  • TokenizerModel
  • MedicalBertForSequenceClassification