2023-06-06-ner_vop_en

docs/_posts/mauro-nievoff/2023-06-06-ner_vop_anatomy_emb_clinical_large_en.md

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+---
+layout: model
+title: Extract Anatomical Entities from Voice of the Patient Documents (embeddings_clinical_large)
+author: John Snow Labs
+name: ner_vop_anatomy_emb_clinical_large
+date: 2023-06-06
+tags: [licensed, clinical, en, ner, vop, anatomy]
+task: Named Entity Recognition
+language: en
+edition: Healthcare NLP 4.4.3
+spark_version: 3.0
+supported: true
+annotator: MedicalNerModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+This model extracts anatomical terms from the documents transferred from the patient’s own sentences.
+
+## Predicted Entities
+
+`BodyPart`, `Laterality`
+
+{:.btn-box}
+[Live Demo](https://demo.johnsnowlabs.com/healthcare/VOICE_OF_THE_PATIENTS/){:.button.button-orange}
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/ner_vop_anatomy_emb_clinical_large_en_4.4.3_3.0_1686074062221.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/ner_vop_anatomy_emb_clinical_large_en_4.4.3_3.0_1686074062221.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+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_large", "en", "clinical/models")\
+    .setInputCols(["sentence", "token"]) \
+    .setOutputCol("embeddings")                
+
+ner = MedicalNerModel.pretrained("ner_vop_anatomy_emb_clinical_large", "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([["Ugh, I pulled a muscle in my neck from sleeping weird last night. It's like a knot in my trapezius and it hurts to turn my head."]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+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_large", "en", "clinical/models")
+    .setInputCols(Array("sentence", "token"))
+    .setOutputCol("embeddings")                
+
+val ner = MedicalNerModel.pretrained("ner_vop_anatomy_emb_clinical_large", "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("Ugh, I pulled a muscle in my neck from sleeping weird last night. It's like a knot in my trapezius and it hurts to turn my head.").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+
+```
+</div>
+
+## Results
+
+```bash
+| chunk     | ner_label   |
+|:----------|:------------|
+| muscle    | BodyPart    |
+| neck      | BodyPart    |
+| trapezius | BodyPart    |
+| head      | BodyPart    |
+```
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_vop_anatomy_emb_clinical_large|
+|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_large|
+
+## 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
+
+```bash
+     label   tp  fp  fn  total  precision  recall   f1
+  BodyPart 2725 236 175   2900       0.92    0.94 0.93
+Laterality  546  62  82    628       0.90    0.87 0.88
+ macro_avg 3271 298 257   3528       0.91    0.90 0.90
+ micro_avg 3271 298 257   3528       0.92    0.93 0.92
+```

docs/_posts/mauro-nievoff/2023-06-06-ner_vop_anatomy_en.md

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+---
+layout: model
+title: Extract Anatomical Entities from Voice of the Patient Documents (embeddings_clinical)
+author: John Snow Labs
+name: ner_vop_anatomy
+date: 2023-06-06
+tags: [licensed, clinical, en, ner, vop, anatomy]
+task: Named Entity Recognition
+language: en
+edition: Healthcare NLP 4.4.3
+spark_version: 3.0
+supported: true
+annotator: MedicalNerModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+This model extracts anatomical terms from the documents transferred from the patient’s own sentences.
+
+## Predicted Entities
+
+`BodyPart`, `Laterality`
+
+{:.btn-box}
+[Live Demo](https://demo.johnsnowlabs.com/healthcare/VOICE_OF_THE_PATIENTS/){:.button.button-orange}
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/ner_vop_anatomy_en_4.4.3_3.0_1686073832453.zip){:.button.button-orange.button-orange-trans.arr.button-icon.hidden}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/clinical/models/ner_vop_anatomy_en_4.4.3_3.0_1686073832453.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+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_anatomy", "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([["Ugh, I pulled a muscle in my neck from sleeping weird last night. It's like a knot in my trapezius and it hurts to turn my head."]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+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_anatomy", "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("Ugh, I pulled a muscle in my neck from sleeping weird last night. It's like a knot in my trapezius and it hurts to turn my head.").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+## Results
+
+```bash
+| chunk     | ner_label   |
+|:----------|:------------|
+| muscle    | BodyPart    |
+| neck      | BodyPart    |
+| trapezius | BodyPart    |
+| head      | BodyPart    |
+```
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_vop_anatomy|
+|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
+
+```bash
+     label   tp  fp  fn  total  precision  recall   f1
+  BodyPart 2682 193 218   2900       0.93    0.92 0.93
+Laterality  539  66  89    628       0.89    0.86 0.87
+ macro_avg 3221 259 307   3528       0.91    0.89 0.90
+ micro_avg 3221 259 307   3528       0.92    0.91 0.92
+```