Extract treatment entities (Voice of the Patients)

Description

This model extracts treatments mentioned in documents transferred from the patient’s own sentences.

Note: ‘wip’ suffix indicates that the model development is work-in-progress and will be finalised and the model performance will improved in the upcoming releases.

Predicted Entities

Drug, Form, Route, Dosage, Duration, Procedure, Frequency, Treatment

Live Demo Open in Colab Download Copy S3 URI

How to use

document_assembler = DocumentAssembler()\
    .setInputCol("text")\
    .setOutputCol("document")

sentence_detector = SentenceDetectorDLModel.pretrained("sentence_detector_dl_healthcare","en","clinical/models")\
    .setInputCols(["document"])\
    .setOutputCol("sentence")

tokenizer = Tokenizer() \
    .setInputCols(["sentence"]) \
    .setOutputCol("token")

word_embeddings = WordEmbeddingsModel().pretrained("embeddings_clinical", "en", "clinical/models")\
    .setInputCols(["sentence", "token"]) \
    .setOutputCol("embeddings")                

ner = MedicalNerModel.pretrained("ner_vop_treatment_wip", "en", "clinical/models") \
    .setInputCols(["sentence", "token", "embeddings"]) \
    .setOutputCol("ner")

ner_converter = NerConverterInternal() \
    .setInputCols(["sentence", "token", "ner"]) \
    .setOutputCol("ner_chunk")
pipeline = Pipeline(stages=[document_assembler,
                            sentence_detector,
                            tokenizer,
                            word_embeddings,
                            ner,
                            ner_converter])

data = spark.createDataFrame([["My grandpa was diagnosed with type 2 diabetes and had to make some changes to his lifestyle. He also takes metformin and glipizide to help regulate his blood sugar levels. It's been a bit of an adjustment, but he's doing well."]]).toDF("text")

result = pipeline.fit(data).transform(data)

val document_assembler = new DocumentAssembler()
    .setInputCol("text")
    .setOutputCol("document")
    
val sentence_detector = SentenceDetectorDLModel.pretrained("sentence_detector_dl_healthcare","en","clinical/models")
    .setInputCols("document")
    .setOutputCol("sentence")
    
val tokenizer = new Tokenizer()
    .setInputCols("sentence")
    .setOutputCol("token")
    
val word_embeddings = WordEmbeddingsModel().pretrained("embeddings_clinical", "en", "clinical/models")
    .setInputCols(Array("sentence", "token"))
    .setOutputCol("embeddings")                
    
val ner = MedicalNerModel.pretrained("ner_vop_treatment_wip", "en", "clinical/models")
    .setInputCols(Array("sentence", "token", "embeddings"))
    .setOutputCol("ner")
    
val ner_converter = new NerConverterInternal()
    .setInputCols(Array("sentence", "token", "ner"))
    .setOutputCol("ner_chunk")

        
val pipeline = new Pipeline().setStages(Array(document_assembler,
                            sentence_detector,
                            tokenizer,
                            word_embeddings,
                            ner,
                            ner_converter))    

val data = Seq("My grandpa was diagnosed with type 2 diabetes and had to make some changes to his lifestyle. He also takes metformin and glipizide to help regulate his blood sugar levels. It's been a bit of an adjustment, but he's doing well.").toDS.toDF("text")

val result = pipeline.fit(data).transform(data)

Results

| chunk     | ner_label   |
|:----------|:------------|
| metformin | Drug        |
| glipizide | Drug        |

Model Information

References

In-house annotated health-related text in colloquial language.

Sample text from the training dataset

Hello,I’m 20 year old girl. I’m diagnosed with hyperthyroid 1 month ago. I was feeling weak, light headed,poor digestion, panic attacks, depression, left chest pain, increased heart rate, rapidly weight loss, from 4 months. Because of this, I stayed in the hospital and just discharged from hospital. I had many other blood tests, brain mri, ultrasound scan, endoscopy because of some dumb doctors bcs they were not able to diagnose actual problem. Finally I got an appointment with a homeopathy doctor finally he find that i was suffering from hyperthyroid and my TSH was 0.15 T3 and T4 is normal . Also i have b12 deficiency and vitamin D deficiency so I’m taking weekly supplement of vitamin D and 1000 mcg b12 daily. I’m taking homeopathy medicine for 40 days and took 2nd test after 30 days. My TSH is 0.5 now. I feel a little bit relief from weakness and depression but I’m facing with 2 new problem from last week that is breathtaking problem and very rapid heartrate. I just want to know if i should start allopathy medicine or homeopathy is okay? Bcs i heard that thyroid take time to start recover. So please let me know if both of medicines take same time. Because some of my friends advising me to start allopathy and never take a chance as i can develop some serious problems.Sorry for my poor english😐Thank you.

Benchmarking

    label   tp   fp  fn  total  precision  recall   f1
     Drug 1299   92 141   1440       0.93    0.90 0.92
     Form  251   36  15    266       0.87    0.94 0.91
    Route   41    5   7     48       0.89    0.85 0.87
   Dosage  342   35  70    412       0.91    0.83 0.87
 Duration 2064  530 246   2310       0.80    0.89 0.84
Procedure  543   67 162    705       0.89    0.77 0.83
Frequency  888  181 191   1079       0.83    0.82 0.83
Treatment  165   54  63    228       0.75    0.72 0.74
macro_avg 5593 1000 895   6488       0.86    0.84 0.85
micro_avg 5593 1000 895   6488       0.85    0.86 0.86