Call for Papers on AI and Related Technologies in the Fight Against COVID-19

Information Technology and Management is seeking submissions to a forthcoming Special Issue on AI and Related Technologies in the Fight Against COVID-19.

COVID-19 disease, caused by the SARS-CoV-2 virus, was identified in December 2019 in China and declared a global pandemic by the WHO on 11 March 2020. Artificial Intelligence (AI) is a potentially powerful tool in the fight against the COVID-19 pandemic. AI and Related technologies can, for present purposes, be defined as Machine Learning (ML) and Intelligent Data Science methodologies considered in Bioinformatics, Risk Analysis and Reliability, complex systems, including socio-economic systems, control, Natural Language Processing (NLP), Computer Vision and Image Understanding applications involving computing systems in successfully managing big data-based models for pattern recognition, explanation, prediction and control. These functions can be useful to recognize (diagnose), predict, control, analyze risk and explain (treat) COVID-19 infections, as well as help manage socio-economic impacts. Since the outbreak of the pandemic, there has been a scramble to use and explore AI, and other intelligent data analytic tools, for these purposes. This pandemic has triggered an unprecedented demand for AI and Related technologies for health management as well as for AI methodologies based emerging socio-economic management technologies solutions and has revealed successful means for population screening, tracking the infection, prioritizing the use and allocation of resources, designing targeted responses, predicting and analyzing the risk as well as analyzing the virus genomics information in order to design proper vaccines and drugs candidates to fight the disease. 

The pandemic is compelling governments and societies to turn toward AI to respond to the crisis and, increasingly, is requiring governments to adopt an open government approach and use AI Related technologies to provide reliable information on global and national COVID-19 developments. With lockdowns and other social distancing measures in effect in many countries, and with more people relying on the internet for information and advice, governments are urged to deploy effective technologies in managing the complex biological and socio-economic systems involved to contain successfully the outbreak. 

A list of topics for the special issue include but not limited to the following:

  • AI/ML for early warnings and alerts 
  • AI/ML techniques in reliability, risk analysis, tracking, and prediction 
  • Data dashboards using AI/ML 
  • AI/ML in diagnosis and prognosis 
  • Advances in bioinformatics, genomics, design of vaccine and drugs candidates, medical decision making, treatment and cures using AI/ML 
  • Socio-economic control and public health management using AI 
  • AI utilization for combating misinformation 
  • AI for Supporting health professionals and workers 
  • AI for community engagement platforms 
  • AI-based supporting knowledge management capacities 
  • AI/ML Research and development support 
  • Recovery planning and Management work using AI/MLs

Manuscript Preparation

We expect full-length submissions with a sufficient level of rigor consistent with the high standard of the journal. The submission can use any appropriate method to analyze problems: analysis of data, mathematical analysis, game theories, etc. The authors should try to keep the papers to be no longer than 38 pages double-spaced in a font size of 11 and in Word or PDF format. Please follow the detailed submission guidelines provided at  https://www.springer.com/journal/10799/submission-guidelines. When answering submission questions, you will specify that your submission is for this special issue.

Submission Timeline

First-round decision: April 30, 2022
Deadline for Revised Papers: June 30, 2022
Final Acceptance: September 15, 2022

Guest Editors

Dr. M. Sundhararajan 
Bharath University, India
E-mail: sundararajan.ece@bharathuniv.ac.in

Dr. Dimitrios A. Karras
National & Kapodistrian University of Athens, Greece
& Epoka University, Albania
E-mail: dakarras@uoa.gr, dkarras@epoka.edu.al

Dr. Jayden Khakurel
University of Turku, Finland
E-mail: jakhak@utu.fi

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