Published on in Vol 7, No 2 (2019): Apr-Jun

Adapting State-of-the-Art Deep Language Models to Clinical Information Extraction Systems: Potentials, Challenges, and Solutions

Adapting State-of-the-Art Deep Language Models to Clinical Information Extraction Systems: Potentials, Challenges, and Solutions

Adapting State-of-the-Art Deep Language Models to Clinical Information Extraction Systems: Potentials, Challenges, and Solutions

Liyuan Zhou   1, 2 , BSc, MSc ;   Hanna Suominen   1, 2, 3, 4 , MSc, PhD ;   Tom Gedeon   1 , BSc (Hons), PhD

1 Research School of Computer Science, College of Engineering and Computer Science, The Australian National University, Canberra, Australia

2 Machine Learning Group, Data61, Commonwealth Scientific and Industrial Research Organisation, Canberra, Australia

3 Faculty of Science and Technology, University of Canberra, Canberra, Australia

4 Department of Future Technologies, Faculty of Science and Engineering, University of Turku, Turku, Finland

Corresponding Author:

  • Liyuan Zhou, BSc, MSc
  • Research School of Computer Science
  • College of Engineering and Computer Science
  • The Australian National University
  • 108 North Road
  • Canberra, 2600
  • Australia
  • Phone: 61 (02)-6125-5111
  • Email: annjouno@gmail.com