SECNLP: A Survey of Embeddings in Clinical Natural Language Processing

Understand

Traditional representations like Bag of words are high dimensional, sparse and ignore the order as well as syntactic and semantic information.

• Distributed vector representations or embeddings map variable length text to dense fixed length vectors as well as capture the prior knowledge which can transferred to downstream tasks.
• Even though embedding has become de facto standard for representations in deep learning based NLP tasks in both general and clinical domains, there is no survey paper which presents a detailed review of embeddings in Clinical Natural Language Processing.
• In this survey paper, we discuss various medical corpora and their characteristics, medical codes and present a brief overview as well as comparison of popular embeddings models.