HCP Consult Classification Pipeline - Voice of the Patient

Description

This pretrained pipeline includes the Medical Bert for Sequence Classification model to identify texts that mention a HCP consult. The pipeline is built on the top of bert_sequence_classifier_vop_hcp_consult 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_hcp_consult_pipeline", "en", "clinical/models")

pipeline.annotate("My son has been to two doctors who gave him antibiotic drops but they also say the problem might related to allergies.")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline

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

val result = pipeline.annotate(My son has been to two doctors who gave him antibiotic drops but they also say the problem might related to allergies.)

Results

| text                                                                                                                   | prediction       |
|:-----------------------------------------------------------------------------------------------------------------------|:-----------------|
| My son has been to two doctors who gave him antibiotic drops but they also say the problem might related to allergies. | Consulted_By_HCP |

Model Information

Model Name: bert_sequence_classifier_vop_hcp_consult_pipeline
Type: pipeline
Compatibility: Healthcare NLP 4.4.3+
License: Licensed
Edition: Official
Language: en
Size: 406.4 MB

Included Models

  • DocumentAssembler
  • TokenizerModel
  • MedicalBertForSequenceClassification