Medical Information Extraction in the Age of Deep Learning.

Journal: Yearbook of medical informatics
Published Date:

Abstract

OBJECTIVES: We survey recent developments in medical Information Extraction (IE) as reported in the literature from the past three years. Our focus is on the fundamental methodological paradigm shift from standard Machine Learning (ML) techniques to Deep Neural Networks (DNNs). We describe applications of this new paradigm concentrating on two basic IE tasks, named entity recognition and relation extraction, for two selected semantic classes-diseases and drugs (or medications)-and relations between them.

Authors

  • Udo Hahn
    Jena University Language & Information Engineering (JULIE) Lab Friedrich-Schiller-Universität Jena, Jena, Germany.
  • Michel Oleynik
    Institute of Mathematics and Statistics, University of São Paulo, São Paulo, Brazil.