Description
Pretrained named entity recognition deep learning model for molecular biology related terms. The SparkNLP deep learning model (MedicalNerModel) is inspired by a former state of the art model for NER: Chiu & Nicols, Named Entity Recognition with Bidirectional LSTM-CNN.
Predicted Entities
DNA, RNA, Cell_type, Cell_line, Protein
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", "en")\
.setInputCols(["document"])\
.setOutputCol("sentence")
tokenizer = Tokenizer()\
.setInputCols(["sentence"])\
.setOutputCol("token")
clinical_embeddings = WordEmbeddingsModel.pretrained("embeddings_clinical_medium", "en", "clinical/models")\
.setInputCols(["sentence", "token"])\
.setOutputCol("embeddings")
ner_model = MedicalNerModel.pretrained("ner_cellular_emb_clinical_medium", "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,
clinical_embeddings,
ner_model,
ner_converter
])
sample_df = spark.createDataFrame([["""Detection of various other intracellular signaling proteins is also described. Genetic characterization of transactivation of the human T-cell leukemia virus type 1 promoter: Binding of Tax to Tax-responsive element 1 is mediated by the cyclic AMP-responsive members of the CREB/ATF family of transcription factors. To achieve a better understanding of the mechanism of transactivation by Tax of human T-cell leukemia virus type 1 Tax-responsive element 1 (TRE-1), we developed a genetic approach with Saccharomyces cerevisiae. We constructed a yeast reporter strain containing the lacZ gene under the control of the CYC1 promoter associated with three copies of TRE-1. Expression of either the cyclic AMP response element-binding protein (CREB) or CREB fused to the GAL4 activation domain (GAD) in this strain did not modify the expression of the reporter gene. Tax alone was also inactive."""]]).toDF("text")
result = pipeline.fit(sample_df).transform(sample_df)
val document_assembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")
val sentence_detector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "en")
.setInputCols("document")
.setOutputCol("sentence")
val tokenizer = new Tokenizer()
.setInputCols("sentence")
.setOutputCol("token")
val clinical_embeddings = WordEmbeddingsModel.pretrained("embeddings_clinical_medium", "en", "clinical/models")
.setInputCols(Array("sentence", "token"))
.setOutputCol("embeddings")
val ner_model = MedicalNerModel.pretrained("ner_cellular_emb_clinical_medium", "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,
clinical_embeddings,
ner_model,
ner_converter))
val sample_data = Seq("""Detection of various other intracellular signaling proteins is also described. Genetic characterization of transactivation of the human T-cell leukemia virus type 1 promoter: Binding of Tax to Tax-responsive element 1 is mediated by the cyclic AMP-responsive members of the CREB/ATF family of transcription factors. To achieve a better understanding of the mechanism of transactivation by Tax of human T-cell leukemia virus type 1 Tax-responsive element 1 (TRE-1), we developed a genetic approach with Saccharomyces cerevisiae. We constructed a yeast reporter strain containing the lacZ gene under the control of the CYC1 promoter associated with three copies of TRE-1. Expression of either the cyclic AMP response element-binding protein (CREB) or CREB fused to the GAL4 activation domain (GAD) in this strain did not modify the expression of the reporter gene. Tax alone was also inactive.""").toDS.toDF("text")
val result = pipeline.fit(sample_data).transform(sample_data)
Results
+-----------------------------------------------------------+-----+---+---------+
|chunk |begin|end|ner_label|
+-----------------------------------------------------------+-----+---+---------+
|intracellular signaling proteins |27 |58 |protein |
|human T-cell leukemia virus type 1 promoter |130 |172|DNA |
|Tax |186 |188|protein |
|Tax-responsive element 1 |193 |216|DNA |
|cyclic AMP-responsive members |237 |265|protein |
|CREB/ATF family |274 |288|protein |
|transcription factors |293 |313|protein |
|Tax |389 |391|protein |
|human T-cell leukemia virus type 1 Tax-responsive element 1|396 |454|DNA |
|TRE-1), |457 |463|DNA |
|lacZ gene |582 |590|DNA |
|CYC1 promoter |617 |629|DNA |
|TRE-1 |663 |667|DNA |
|cyclic AMP response element-binding protein |695 |737|protein |
|CREB |740 |743|protein |
|CREB |749 |752|protein |
|GAL4 activation domain |767 |788|protein |
|GAD |791 |793|protein |
|reporter gene |848 |860|DNA |
|Tax |863 |865|protein |
+-----------------------------------------------------------+-----+---+---------+
Model Information
| Model Name: | ner_cellular_emb_clinical_medium |
| Compatibility: | Healthcare NLP 4.4.2+ |
| License: | Licensed |
| Edition: | Official |
| Input Labels: | [sentence, token, embeddings] |
| Output Labels: | [ner] |
| Language: | en |
| Size: | 2.8 MB |
References
Trained on the JNLPBA corpus containing more than 2.404 publication abstracts. https://www.geniaproject.org/
Benchmarking
label precision recall f1-score support
cell_line 0.59 0.80 0.68 1489
cell_type 0.89 0.76 0.82 4912
protein 0.80 0.90 0.85 9841
RNA 0.79 0.83 0.81 305
DNA 0.78 0.86 0.82 2845
micro-avg 0.80 0.85 0.82 19392
macro-avg 0.77 0.83 0.79 19392
weighted-avg 0.80 0.85 0.82 19392