Embeddings Clinical

Description

Word Embeddings lookup annotator that maps tokens to vectors

Predicted Entities

Word2Vec feature vectors based on embeddings_clinical.

Download

How to use

model = WordEmbeddingsModel.pretrained("embeddings_clinical","en","clinical/models")\
	.setInputCols("document","token")\
	.setOutputCol("word_embeddings")
val model = WordEmbeddingsModel.pretrained("embeddings_clinical","en","clinical/models")
	.setInputCols("document","token")
	.setOutputCol("word_embeddings")

Model Information

Name: embeddings_clinical
Type: WordEmbeddingsModel
Compatibility: Spark NLP 2.4.0+
License: Licensed
Edition: Official
Input labels: [document, token]
Output labels: [word_embeddings]
Language: en
Dimension: 200.0

Data Source

Trained on PubMed corpora https://www.nlm.nih.gov/databases/download/pubmed_medline.html