VOC-DL: Deep learning prediction model for COVID-19 based on VOC virus variants.

Journal: Computer methods and programs in biomedicine
Published Date: Jun 30, 2022

Abstract

BACKGROUND AND OBJECTIVE: The ever-mutating COVID-19 has infected billions of people worldwide and seriously affected the stability of human society and the world economic development. Therefore, it is essential to make long-term and short-term forecasts for COVID-19. However, the pandemic situation in different countries and regions may be dominated by different virus variants, and the transmission capacity of different virus variants diversifies. Therefore, there is a need to develop a predictive model that can incorporate mutational information to make reasonable predictions about the current pandemic situation.

Authors

  • Zhifang Liao
    School of Computer Science and Engineering, Central South University, Changsha, 410075, China. Electronic address: zfliao@csu.edu.cn.
  • Yucheng Song
    School of Computer Science and Engineering, Central South University, Changsha, China.
  • Shengbing Ren
    School of Computer Science and Engineering, Central South University, Changsha, China.
  • Xiaomeng Song
    School of Computer Science and Engineering, Central South University, Changsha 410083, China.
  • Xiaoping Fan
    Hunan University of Finance and Economics, Changsha, China. Electronic address: xpfan@mail.csu.edu.cn.
  • Zhining Liao
    Nuffield health Research Group, Nuffield Health, Ashley Avenue, Epsom, Surrey, KT18 5AL, UK. Electronic address: zhining.liao@nuffieldhealth.com.

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