Description
Classify text/sentence in two categories:
-
True: The sentence is talking about a possible ADE -
False: The sentences doesn’t have any information about an ADE.
Classified Labels
True, False
Live Demo Open in Colab Download
How to use
...
embeddings = BertEmbeddings.pretrained('biobert_pubmed_base_cased')\
.setInputCols(["document", 'token'])\
.setOutputCol("word_embeddings")
sentence_embeddings = SentenceEmbeddings() \
.setInputCols(["document", "word_embeddings"]) \
.setOutputCol("sentence_embeddings") \
.setPoolingStrategy("AVERAGE")
classifier = ClassifierDLModel.pretrained('classifierdl_ade_biobert', 'en', 'clinical/models')\
.setInputCols(['document', 'token', 'sentence_embeddings']).setOutputCol('class')
nlp_pipeline = Pipeline(stages=[document_assembler, tokenizer, embeddings, sentence_embeddings, classifier])
light_pipeline = LightPipeline(nlp_pipeline.fit(spark.createDataFrame([['']]).toDF("text")))
annotations = light_pipeline.fullAnnotate(["I feel a bit drowsy & have a little blurred vision after taking an insulin", "I feel great after taking tylenol"])
...
val embeddings = BertEmbeddings.pretrained('biobert_pubmed_base_cased')
.setInputCols(Array("document", 'token'))
.setOutputCol("word_embeddings")
val sentence_embeddings = SentenceEmbeddings()
.setInputCols(Array("document", "word_embeddings"))
.setOutputCol("sentence_embeddings")
.setPoolingStrategy("AVERAGE")
val classifier = ClassifierDLModel.pretrained('classifierdl_ade_biobert', 'en', 'clinical/models')
.setInputCols(Array('document', 'token', 'sentence_embeddings')).setOutputCol('class')
val pipeline = new Pipeline().setStages(Array(document_assembler, tokenizer, embeddings, sentence_embeddings, classifier))
val result = pipeline.fit(Seq.empty["I feel a bit drowsy & have a little blurred vision after taking an insulin", "I feel great after taking tylenol"].toDS.toDF("text")).transform(data)
Results
| | text | label |
|--:|:---------------------------------------------------------------------------|:------|
| 0 | I feel a bit drowsy & have a little blurred vision after taking an insulin | True |
| 1 | I feel great after taking tylenol | False |
Model Information
| Model Name: | classifierdl_ade_biobert |
| Compatibility: | Spark NLP for Healthcare 2.7.1+ |
| License: | Licensed |
| Edition: | Official |
| Input Labels: | [sentence_embeddings] |
| Output Labels: | [class] |
| Language: | en |
| Dependencies: | biobert_pubmed_base_cased |
Data Source
Trained on a custom dataset comprising of CADEC, DRUG-AE and Twimed.
Benchmarking
precision recall f1-score support
False 0.96 0.94 0.95 6923
True 0.71 0.79 0.75 1359
micro avg 0.91 0.91 0.91 8282
macro avg 0.83 0.86 0.85 8282
weighted avg 0.92 0.91 0.91 8282