Deep learning modelling to forecast emergency department visits using calendar, meteorological, internet search data and stock market price.

Journal: Computer methods and programs in biomedicine
Published Date:

Abstract

BACKGROUND: Accurate prediction of hospital emergency department (ED) patient visits and acuity levels have potential to improve resource allocation including manpower planning and hospital bed allocation. Internet search data have been used in medical applications like disease pattern prediction and forecasting ED volume. Past studies have also found stock market price positively correlated with ED volume.

Authors

  • Chua Ming
    Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  • Geraldine Jw Lee
    Department of Statistics and Data Science, Faculty of Science, National University of Singapore, Singapore.
  • Yao Neng Teo
    Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  • Yao Hao Teo
    Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  • Xinyan Zhou
    Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  • Elizabeth Sy Ho
    Department of Computer Science and Technology, University of Cambridge, United Kingdom.
  • Emma Ms Toh
    Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  • Marcus Eng Hock Ong
    Department of Emergency Medicine, Singapore General Hospital, Singapore, Singapore. marcus.ong.e.h@sgh.com.sg.
  • Benjamin Yq Tan
    Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Division of Neurology, Department of Medicine, National University Hospital, Singapore.
  • Andrew Fw Ho
    Department of Emergency Medicine, Singapore General Hospital, Singapore; Pre-Hospital and Emergency Research Centre, Duke-NUS Medical School, Singapore. Electronic address: Andrew.ho@duke-nus.edu.sg.