Tech Science Press Journals Now Available on PubScholar Platform
ResearchGate and Tech Science Press announce new Journal Home partnership
SDHM Selected for the Jiangsu Science and Technology Journal Excellence Action Plan
JCR 2024 Released: 13 TSP Journals Achieve Latest Impact Factors
23 Mar 2020
Computers, Materials & Continua
Computers, Materials & Continua (CMC) (ISSN: 1546-2218, Tech Science Press, USA. SCI: 2018 IF 3.024, JCR: Q1) is dedicated to publishing rigorously peer-reviewed, high quality scientific articles covering the areas of computer networks, artificial intelligence, big data processing and management, software engineering, multimedia, cyber security, internet of things, materials genome, integrated materials science, and data analysis, modeling, designing, and manufacturing of modern functional and multifunctional materials. Novel high-performance computing methods, big data analysis, and artificial intelligence that advance material technologies are especially welcome.
Call for Papers
Special Issue on Artificial Intelligence and Information Technologies for COVID-19
The COVID-19 disease has reached pandemic proportion, according to World Health Organization (WHO) situation report 61. WHO confirms 266,073 cases worldwide as of , with a cumulative death toll of 11,184. Unfortunately, both numbers are expected to continue to rise.
The goal of this special issue of Computers, Materials & Continua (CMC) Journal is to offer enlightening research and effective tools that can help track and predict the spread of the virus, prevent the pandemic from spreading further, and better allocate scarce resources to optimize patient outcomes. This special issue is jointly established by the CMC and the Engineering Research Center of Digital Forensics of Ministry of Education to call upon experts from the fields of big data and artificial intelligence to conduct research on COVID-19 tracking, suppression, and treatment strategies. This special issue invites high quality articles to share and discuss the latest developments and future trends of prevention and treatment methods which are based on the analysis of data. Topics include, but are not limited to, the following areas:
• Artificial intelligence in COVID-19 drug discovery and development
• Big data in COVID-19 analysis
• Knowledge representation in COVID-19 analysis
• Pattern recognition in COVID-19 risk analysis
• Machine learning for COVID-19 tracking and prediction models
• Applications of the Internet of Things in healthcare
• Computer vision in COVID-19-related medical imaging
• Computer vision in COVID-19 treatment simulation
• Distributed system in COVID-19 treatment simulation
• Information technologies in COVID-19 patient tracking
• Information technologies in COVID-19 patient monitoring
• Information technologies in hospital management during an epidemic or pandemic
• Software and/or Hardware in computer-assisted surgery
• Social network analysis for contact tracing
• Artificial intelligence security in analysis of public health emergencies
• Security and privacy of big data in public health emergencies
• Secure and privacy-preserving analysis of data in public health emergencies
• Social media security and forensics in COVID-19 risk management
• Optimizing allocation of resources during a pandemic or epidemic
• Telemedicine for managing non-emergent patients
• Information technologies to support vaccine development
• Predictive Analytics in COVID-19 risk profiling
• Predictive Analytics in patients utilization patterns
• Predictive Analytics in aiding diagnosis
Submission Guidelines:
Authors should prepare their manuscript according to the guide for authors described at the journal site (http://techscience.com/journal/cmc). All papers will be peer-reviewed by independent reviewers. The submission website is http://tspsubmission.com/index.php/cmc. Authors should select “AIIT for COVID-19” when they reach the “Paper Section” step in the submission process.
Important Dates:
• Submission deadline: April 30, 2020
• Publication: May or June, 2020
Guest Editors:
• Xiaorui Zhang, Nanjing University of Information Science & Technology, China
• Zhihua Xia, Engineering Research Center of Digital Forensics, Ministry of Education, China
• Suzanne McIntosh, New York University, USA
• Anasse Bari, New York University, USA
• Lixin Xie, PLA General Hospital, China