AI and COVID-19
Martin Michalowski, University of Minnesota, USA
Robert Moskovitch, Ben-Gurion University, Israel
Nitesh Chawla, University of Notre Dame, USA
The recent outbreak of the novel Coronavirus 2019 (COVID-19) originated in Wuhan, China and within several months spread globally, resulting in millions of confirmed cases and hundreds of thousands of deaths worldwide. The human race is facing one of the most meaningful public health emergencies in the modern era caused by the COVID-19 pandemic. This pandemic introduced various challenges, from lock-downs with significant economic costs to fundamentally altering the way of life for many people around the world. The battle to understand and control the virus is still at its early stages. The uncertainty of why some patients are infected and experience severe symptoms, others are infected but asymptomatic, and others are not infected at all makes managing this pandemic very challenging. Furthermore, the development of treatments and vaccines relies on knowledge generated from an ever evolving and expanding information space.
Given the availability of digital data in the modern era, artificial intelligence (AI) is a meaningful tool for addressing the various challenges introduced by this unexpected pandemic. Some of the challenges include: outbreak prediction, risk modeling (who will get infected and develop symptoms), testing strategy optimization, drug development, treatment repurposing, vaccine development, and others. Since the detected spread of COVID- 19, a meaningful amount of research has been performed that used AI-based methods in the analysis of data, in the attempt to repurpose existing drugs, in understanding who is susceptible to the virus and who will get severe symptoms, and even in developing a cure.
In this special track on Artificial Intelligence and COVID-19, we invite scholars and clinicians to present leading research focusing on the solutions data science and AI provide to address challenges related to the global pandemic, and on relevant deployments and experiences in gearing AI to cope with COVID-19. This special track is interested in original contributions regarding the development of theory, methods, systems, and applications for solving problems related to COVID-19 including AI approaches in biomedical informatics, molecular medicine, and health-care organizational aspects. All authors are required to highlight the value their work created for the patient, provider, and institution through its clinical relevance. Topics of interest include the following AI topics in the context of COVID-19, but not limited to:
- Deep Learning
- Active Learning
- Knowledge Representation
- Natural Language Processing
- Predictive Modeling
- Image Processing
- Unsupervised Learning
- Temporal Data Analysis
- Information Retrieval
- Economic Utilities
- Risk Analysis
When submitting a manuscript to the special track, please select “AI and COVID-19” during submission.
Key Dates (revised)
In light of the ongoing pandemic, this special track continues to be very pertinent. As such, the special track dates have been extended to accommodate additional manuscript submissions. Submissions that conformed to the original dates will be kept on that schedule. Contents of the special track will be made available as articles are accepted.
Deadline for Submission: 4 April, 2021
Reviews Due: 28 May, 2021
Final Decision: 28 June, 2021