2021-11-03-ner_profiling_biobert_en

docs/_posts/muhammetsnts/2021-11-03-ner_profiling_biobert_en.md

@@ -0,0 +1,101 @@
+---
+layout: model
+title: Named Entity Recognition Profiling (Biobert)
+author: John Snow Labs
+name: ner_profiling_biobert
+date: 2021-11-03
+tags: [ner, ner_profiling, clinical, licensed, en, biobert]
+task: Pipeline Healthcare
+language: en
+edition: Spark NLP for Healthcare 3.3.1
+spark_version: 2.4
+supported: true
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+This pipeline can be used to explore all the available pretrained NER models at once. When you run this pipeline over your text, you will end up with the predictions coming out of each pretrained clinical NER model trained with `biobert_pubmed_base_cased`. It has been updated by adding NER model outputs to the previous version.
+
+Here are the NER models that this pretrained pipeline includes: `ner_jsl_enriched_biobert`, `ner_clinical_biobert`, `ner_chemprot_biobert`, `ner_jsl_greedy_biobert`, `ner_bionlp_biobert`, `ner_human_phenotype_go_biobert`, `jsl_rd_ner_wip_greedy_biobert`, `ner_posology_large_biobert`, `ner_risk_factors_biobert`, `ner_anatomy_coarse_biobert`, `ner_deid_enriched_biobert`, `ner_human_phenotype_gene_biobert`, `ner_jsl_biobert`, `ner_events_biobert`, `ner_deid_biobert`, `ner_posology_biobert`, `ner_diseases_biobert`, `jsl_ner_wip_greedy_biobert`, `ner_ade_biobert`, `ner_anatomy_biobert`, `ner_cellular_biobert` .
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+[Open in Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/11.2.Pretrained_NER_Profiling_Pipelines.ipynb){:.button.button-orange.button-orange-trans.co.button-icon}
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/clinical/models/ner_profiling_biobert_en_3.3.1_2.4_1635977081207.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+from sparknlp.pretrained import PretrainedPipeline
+
+ner_profiling_pipeline = PretrainedPipeline('ner_profiling_biobert', 'en', 'clinical/models')
+
+result = ner_profiling_pipeline.annotate("A 28-year-old female with a history of gestational diabetes mellitus diagnosed eight years prior to presentation and subsequent type two diabetes mellitus ( T2DM ), one prior episode of HTG-induced pancreatitis three years prior to presentation , associated with an acute hepatitis , and obesity with a body mass index ( BMI ) of 33.5 kg/m2 , presented with a one-week history of polyuria , polydipsia , poor appetite , and vomiting .")
+```
+```scala
+import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
+
+val ner_profiling_pipeline = PretrainedPipeline('ner_profiling_biobert', 'en', 'clinical/models')
+
+val result = ner_profiling_pipeline.annotate("A 28-year-old female with a history of gestational diabetes mellitus diagnosed eight years prior to presentation and subsequent type two diabetes mellitus ( T2DM ), one prior episode of HTG-induced pancreatitis three years prior to presentation , associated with an acute hepatitis , and obesity with a body mass index ( BMI ) of 33.5 kg/m2 , presented with a one-week history of polyuria , polydipsia , poor appetite , and vomiting .")
+```
+</div>
+
+## Results
+
+```bash
+ ******************** ner_diseases_biobert Model Results ******************** 
+
+[('gestational diabetes mellitus', 'Disease'), ('type two diabetes mellitus', 'Disease'), ('T2DM', 'Disease'), ('HTG-induced pancreatitis', 'Disease'), ('hepatitis', 'Disease'), ('obesity', 'Disease'), ('polyuria', 'Disease'), ('polydipsia', 'Disease'), ('poor appetite', 'Disease'), ('vomiting', 'Disease')]
+
+
+ ******************** ner_events_biobert Model Results ******************** 
+
+[('gestational diabetes mellitus', 'PROBLEM'), ('eight years', 'DURATION'), ('presentation', 'OCCURRENCE'), ('type two diabetes mellitus ( T2DM', 'PROBLEM'), ('HTG-induced pancreatitis', 'PROBLEM'), ('three years', 'DURATION'), ('presentation', 'OCCURRENCE'), ('an acute hepatitis', 'PROBLEM'), ('obesity', 'PROBLEM'), ('a body mass index', 'TEST'), ('BMI', 'TEST'), ('presented', 'OCCURRENCE'), ('a one-week', 'DURATION'), ('polyuria', 'PROBLEM'), ('polydipsia', 'PROBLEM'), ('poor appetite', 'PROBLEM'), ('vomiting', 'PROBLEM')]
+
+
+ ******************** ner_jsl_biobert Model Results ******************** 
+
+[('28-year-old', 'Age'), ('female', 'Gender'), ('gestational diabetes mellitus', 'Diabetes'), ('eight years prior', 'RelativeDate'), ('type two diabetes mellitus', 'Diabetes'), ('T2DM', 'Disease_Syndrome_Disorder'), ('HTG-induced pancreatitis', 'Disease_Syndrome_Disorder'), ('three years prior', 'RelativeDate'), ('acute', 'Modifier'), ('hepatitis', 'Disease_Syndrome_Disorder'), ('obesity', 'Obesity'), ('body mass index', 'BMI'), ('BMI ) of 33.5 kg/m2', 'BMI'), ('one-week', 'Duration'), ('polyuria', 'Symptom'), ('polydipsia', 'Symptom'), ('poor appetite', 'Symptom'), ('vomiting', 'Symptom')]
+
+
+ ******************** ner_clinical_biobert Model Results ******************** 
+
+[('gestational diabetes mellitus', 'PROBLEM'), ('subsequent type two diabetes mellitus ( T2DM', 'PROBLEM'), ('HTG-induced pancreatitis', 'PROBLEM'), ('an acute hepatitis', 'PROBLEM'), ('obesity', 'PROBLEM'), ('a body mass index ( BMI )', 'TEST'), ('polyuria', 'PROBLEM'), ('polydipsia', 'PROBLEM'), ('poor appetite', 'PROBLEM'), ('vomiting', 'PROBLEM')]
+
+
+ ******************** ner_risk_factors_biobert Model Results ******************** 
+
+[('diabetes mellitus', 'DIABETES'), ('subsequent type two diabetes mellitus', 'DIABETES'), ('obesity', 'OBESE')]
+
+...
+```
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_profiling_biobert|
+|Type:|pipeline|
+|Compatibility:|Spark NLP for Healthcare 3.3.1+|
+|License:|Licensed|
+|Edition:|Official|
+|Language:|en|
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- TokenizerModel
+- BertEmbeddings
+- MedicalNerModel (x21)
+- NerConverter (x21)
+- Finisher