COVID-19, known as the Corona Virus Disease 19, is a disease which created a significant impact by being a cause of death to the majority of the deceased population of the world in 2019-2020. The primary source for the transmission of the disease, detection and treatment methods are still unknown. Lots of the details about this virus is still missing. How it spreads, prevention measures and vaccinations issues need to be further investigated. In this field, Artificial Intelligence (AI) and computer-assisted paradigms can play a key role in achieving many effective and efficient solutions. Such intelligent techniques can achieve very effective diagnosis for the COVID-19 and alike diseases in the biomedical field by even being better than physicians. It can examine extended counts of the possibilities and exchange the found results in timely manners. Current smart cities infrastructure includes a number of smart devices having the sensing and data routing capabilities to communicate with each other using various protocols, allowing the disease updates to be accessed any-time from anywhere. They have the potential to provide innovative services which could not be possible without the progress made in the AI field.
This venue aims to solicit original research articles, which contributes to the current state of the art by reporting results for the used AI techniques in the problem scope of computer networks-assisted COVID-19 and alike diagnosis. It will shed the light on potential mobile Internet, big data, artificial intelligence, cloud computing and other modern information technology that can build the required online and cost-efficient medical service platforms.
Topics of interest include, but are not limited to, the following scope:
- AI in the Internet of Medical Things (IoMT)
- AI in IoT-oriented medical applications
- AI and IoT paradigms in sustainable education systems
- AI/IoT solutions in smart cities traffic systems
- Deep Learning for COVID-19 and alike diagnosis
- Neural Network for medical diagnosis
- AI-oriented Internet hospital and online diagnosis
- Collaboration of Image Progressing and ML for COVID-19 and alike diagnosis
- Collaboration of Computer Communication and ML for COVID-19 and alike diagnosis,
- AI and ML in Medical and Critical applications
- Use cases of computer-assisted COVID-19 and alike detection systems,
- COVID-19 Patient Care and Treatment using ML-oriented systems,
- Emerging Networks solutions for improved medical diagnosis results,
- Intelligent Hardware solutions for COVID-19 and alike diagnosis,
- Effective use of computer communication and ML for solving open medical problems,
- Next Generation Networks (NGNs) and ML solutions for medical diagnosis.
- Security and privacy aspects in medical diagnosis.
- Manuscript submission deadline: 2nd July., 2021
- Notification of acceptance: 3rd Sept., 2021
- Submission of final revised paper: 3rd Oct., 2021
- Publication of special issue (tentative): 4th Nov., 2021
Authors should follow the MONET Journal manuscript format described at the journal site. Manuscripts should be submitted on-line through http://www.editorialmanager.com/mone/.
A copy of the manuscript should also be emailed to the Guest Editors at the following email firstname.lastname@example.org
Prof. Dr. Fadi Al-Turjman
Research Centre for AI and IoT, Near East University, Turkey
Prof. Dr. Fadi Al-Turjman received his Ph.D. in computer science from Queen’s University, Kingston, Ontario, Canada, in 2011. He is a full professor and a research center director at Near East University, Nicosia, Cyprus. Prof. Al-Turjman is a leading authority in the areas of smart/intelligent, wireless, and mobile networks’ architectures, protocols, deployments, and performance evaluation. His publication history spans over 250 publications in journals, conferences, patents, books, and book chapters, in addition to numerous keynotes and plenary talks at flagship venues. He has authored and edited more than 25 books about cognition, security, and wireless sensor networks’ deployments in smart environments, published by Taylor and Francis, Elsevier, and Springer. He has received several recognitions and best papers’ awards at top international conferences. He also received the prestigious Best Research Paper Award from Elsevier Computer Communications Journal for the period 2015-2018, in addition to the Top Researcher Award for 2018 at Antalya Bilim University, Turkey. Prof. Al-Turjman has led a number of international symposia and workshops in flagship communication society conferences. Currently, he serves as an associate editor and the lead guest/associate editor for several well reputed journals, including the IEEE Communications Surveys and Tutorials (IF 23.9) and the Elsevier Sustainable Cities and Society (IF 5.7).