IEEE Transactions论文征集：COVID-19的人工智能专题

2020 年 5 月 11 日 学术头条

The Coronavirus Disease 2019 (COVID-19) pandemic has caused extreme strains on health systems, public health infrastructure, and economies of many countries. As of April 2020, millions of people have been infected, and more than two billion globally are staying home to avoid coronavirus. This raging pandemic continues to disrupt our lives while the scientific community is rushing to find a cure for COVID-19. We can leverage artificial intelligence (AI) and big data to help combat the COVID-19 pandemic. For example, ongoing AI efforts aim to expedite the development of a safe and effective COVID-19 vaccine, use networks to repurpose drugs for COVID-19, predict antibacterial properties of new molecules, and design machine-readable datasets of scientific literature on the novel coronavirus.

This special issue will provide a forum for AI and data science research in understanding, predicting, forecasting, and modeling the COVID-19 crisis and potential future outbreaks. We expect novel data science research aimed at elucidating the basic biology of the coronavirus and other emerging pathogens as well as research aimed at curbing the impact of COVID-19 on the economy, healthcare, and society. We will take this opportunity to connect researchers who work around the world to contain and conquer the global health crisis.

The special issue invites original research in the fields of AI, data mining, machine learning, and network science, describing how AI and data can help with the COVID-19 crisis and emerging pathogens. We especially welcome interdisciplinary submissions at the interface of machine learning and key COVID-19 related fields, including biology, medicine, epidemiology, economy, and social sciences. In this context, topics of interest include, but are not limited to:

AI for COVID-19
Machine learning for COVID-19
Deep learning for COVID-19
Network science for COVID-19
COVID-19 drug discovery, repurposing, and the search for COVID-19 cure
Machine learning methods for antiviral molecule discovery
Data analytics for managing supply chain risks and economic disruption from the spread of COVID-19
Conversational AI and virtual agents to keep businesses operating during COVID-19 crisis
Data science methods for modeling symptoms, treatments, and outcomes of COVID-19 patients
Data science methods for effective testing and contact-tracing during an epidemic
Big-data methods for mitigating the impact of COVID-19 on the healthcare systems
Machine-learning methods for developing new diagnostic tools, vaccines, and therapies; understanding COVID-19 epidemiology; and improving clinical management
Methods for knowledge discovery from coronavirus-related research
New datasets and benchmarks for COVID-19 and future epidemics

In light of the urgent need for COVID-19 therapeutics and data-driven solutions to mitigate the COVID-19 pandemic, the special issue will do a fast-track peer review to accelerate the publication process. We will aim for author notification within five weeks of the paper submission.