Ner DL Model Diseases

Description

Named Entity recognition annotator allows for a generic model to be trained by utilizing a deep learning algorithm (Char CNNs - BiLSTM - CRF - word embeddings) inspired on a former state of the art model for NER: Chiu & Nicols, Named Entity Recognition with Bidirectional LSTM,CNN. Pretrained named entity recognition deep learning model for diseases.

Predicted Entities

Disease

Open in ColabDownload

How to use

model = NerDLModel.pretrained("ner_diseases","en","clinical/models")\
	.setInputCols("sentence","token","word_embeddings")\
	.setOutputCol("ner")
val model = NerDLModel.pretrained("ner_diseases","en","clinical/models")
	.setInputCols("sentence","token","word_embeddings")
	.setOutputCol("ner")

Model Information

Name: ner_diseases  
Type: NerDLModel  
Compatibility: Spark NLP 2.4.4 +  
License: Licensed  
Edition: Official  
Input labels: [sentence, token, word_embeddings]  
Output labels: [ner]  
Language: en  
Case sensitive: False  
Dependencies: embeddings_clinical  

Data Source

Trained on i2b2 with embeddings_clinical.