Extract Temporal Entities from Voice of the Patient Documents (embeddings_clinical)

Description

This model extracts temporal references from the documents transferred from the patient’s own sentences.

Predicted Entities

DateTime, Duration, Frequency

Live Demo Open in Colab 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_temporal", "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([["I broke my arm playing football last month and had to get surgery in the orthopedic department. The cast just came off yesterday and I'm excited to start physical therapy and get back to the game."]]).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_temporal", "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("I broke my arm playing football last month and had to get surgery in the orthopedic department. The cast just came off yesterday and I'm excited to start physical therapy and get back to the game.").toDS.toDF("text")

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

Results

| chunk      | ner_label   |
|:-----------|:------------|
| last month | DateTime    |
| yesterday  | DateTime    |

Model Information

Model Name: ner_vop_temporal
Compatibility: Healthcare NLP 4.4.3+
License: Licensed
Edition: Official
Input Labels: [sentence, token, embeddings]
Output Labels: [ner]
Language: en
Size: 3.8 MB
Dependencies: embeddings_clinical

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
 DateTime 4056  655 346   4402       0.86    0.92 0.89
 Duration 2008  371 302   2310       0.84    0.87 0.86
Frequency  879  157 200   1079       0.85    0.81 0.83
macro_avg 6943 1183 848   7791       0.85    0.87 0.86
micro_avg 6943 1183 848   7791       0.85    0.89 0.87