Clinical QA BioGPT (JSL - conversational)


This model is based on BioGPT finetuned with medical conversations happening in a clinical settings and can answer clinical questions related to symptoms, drugs, tests, and diseases. The difference between this model and biogpt_chat_jsl is that this model produces more concise/smaller response.

Predicted Entities

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How to use

document_assembler = DocumentAssembler() \
    .setInputCol("text") \
gpt_qa = MedicalTextGenerator.pretrained("biogpt_chat_jsl_conversational", "en", "clinical/models")\
pipeline = Pipeline().setStages([document_assembler, gpt_qa])

data = spark.createDataFrame([["How to treat asthma ?"]]).toDF("text")

val document_assembler = new DocumentAssembler()

val summarizer  = MedicalTextGenerator.pretrained("biogpt_chat_jsl_conversational", "en", "clinical/models")

val pipeline = new Pipeline().setStages(Array(document_assembler, summarizer))

val text = "How to treat asthma ?"

val data = Seq(Array(text)).toDS.toDF("text")

val result =


question: How to treat asthma ? answer: You have to take montelukast + albuterol tablet once or twice in day according to severity of symptoms. Montelukast is used as a maintenance therapy to relieve symptoms of asthma. Albuterol is used as a rescue therapy when symptoms are severe. You can also use inhaled corticosteroids ( ICS ) like budesonide or fluticasone for long term treatment.

Model Information

Model Name: biogpt_chat_jsl_conversational
Compatibility: Healthcare NLP 4.4.0+
License: Licensed
Edition: Official
Language: en
Size: 1.4 GB
Case sensitive: true