A novel multimodal fusion framework for early diagnosis and accurate classification of COVID-19 patients using X-ray images and speech signal processing techniques.

Journal: Computer methods and programs in biomedicine
Published Date: Nov 1, 2022

Abstract

BACKGROUND AND OBJECTIVE: COVID-19 outbreak has become one of the most challenging problems for human being. It is a communicable disease caused by a new coronavirus strain, which infected over 375 million people already and caused almost 6 million deaths. This paper aims to develop and design a framework for early diagnosis and fast classification of COVID-19 symptoms using multimodal Deep Learning techniques.

Authors

  • Santosh Kumar
    University of Memphis.
  • Mithilesh Kumar Chaube
    Department of Mathematical Sciences, International Institute of Information Technology, Naya Raipur, Chhattishgarh, India. Electronic address: mithilesh@iiitnr.edu.in.
  • Saeed Hamood Alsamhi
    Software Research Institute, Technological University of the Shannon, Midlands Midwest, N37HD68 Athlone, Ireland.
  • Sachin Kumar Gupta
    School of Electronics and Communication Engineering, Shri Mata Vaishno Devi University, Katra, India. Electronic address: sachin.gupta@smvdu.ac.in.
  • Mohsen Guizani
    Machine Learning Department, Mohamed Bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates. Electronic address: mguizani@ieee.org.
  • Raffaele Gravina
  • Giancarlo Fortino
    Department of Informatics, Modeling, Electronics and Systems, University of Calabria, 87036 Rende CS, Italy.

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