Guest Editors
Dr. Junaid Shuja, COMSATS University Islamabad, Pakistan.
Dr. Ali Kashif Bashir, Manchester Metropolitan University, United Kingdom.
Dr. Muhammad Mazhar Ullah Rathore, Hamad Bin Khalifa University, Qatar.
Dr. Teh Ying Wah, University of Malaya, Malaysia.
Summary
The COVID-19 virus has been declared pandemic by World Health Organization with more than 150 million cases and 5 million deaths worldwide as of 1 December 2021. The COVID-19 virus cases have increased exponentially and formed mutations indicating its highly contagious characteristics. Recently, the focus of researchers has shifted towards sustainable and long-term solutions of COVID and pandemics in general. Sustainable AI solutions focus on addressing issues of COVID-19 with emerging virus variants, are cost efficient, deployable in general practice (hospitals, emergency response centers, etc), and address long-term objectives to mitigate and contain the pandemic.
Currently, the human community at large has no other option than to follow either containment or mitigation strategy to stop its contagious spread. The great pandemic affecting billions of lives economically and socially has motivated the scientific community to come up with solutions based on computer-aided digital technologies for diagnosis, prevention, and estimation of COVID-19. The main contributions are coming from the Artificial Intelligence (AI) for detection and analysis of the COVID-19 cases from both imaging sensors (CT and X-ray) and clinical data. In addition, such AI based solutions can also be proposed for tracking positive cases, identifying social distances and analyzing emotional behavior. However, the AI solutions should address the characteristics of new COVID-19 variants to propose solutions that are sustainable.
This special issue calls for original and innovative AI-based techniques to address the recent challenges caused by COVID-19. This special issue will focus on research works addressing sustainable and long-term solutions. Topics of interest include but are not limited to the following:
• Sustainable AI/ML application for COVID diagnosis
• AI for emerging COVID-19 variants
• Deep learning methods for COVID-19
• Analysis of human Immunity for COVID resistance.
• Sustainable and deployable solutions based on CT/Xray/MRI data
• Smart contact tracing solutions of COVID
• Privacy preserving solutions for COVID-19 data
• Epidemiological analysis of COVID-19
• Application of Blockchain towards COVID-19 contact tracing
• Long-term Data curation for COVID-19 biomedical analysis
• Smart city, IoT, and Edge based solutions for COVID-19 beyond pandemic
• Federated learning based techniques
• Proposals for network load management in case of distance learning
• Long-term COVID-19 case predictions
• Time-series data analysis of COVID-19
• Social Media analysis for COVID-19 risk assessment
Keywords
Sustainable computing, COVID-19, Artificial Intelligence, Machine Learning, Deep Learning
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