Recurrent neural networks with specialized word embeddings for health-domain named-entity recognition.

Journal: Journal of biomedical informatics
Published Date:

Abstract

BACKGROUND: Previous state-of-the-art systems on Drug Name Recognition (DNR) and Clinical Concept Extraction (CCE) have focused on a combination of text "feature engineering" and conventional machine learning algorithms such as conditional random fields and support vector machines. However, developing good features is inherently heavily time-consuming. Conversely, more modern machine learning approaches such as recurrent neural networks (RNNs) have proved capable of automatically learning effective features from either random assignments or automated word "embeddings".

Authors

  • IƱigo Jauregi Unanue
    University of Technology Sydney (UTS), Australia; Capital Markets Cooperative Research Centre (CMCRC), Australia. Electronic address: ijauregi@cmcrc.com.
  • Ehsan Zare Borzeshi
    Capital Markets Cooperative Research Centre (CMCRC), Australia.
  • Massimo Piccardi
    University of Technology Sydney (UTS), Australia.