Mapping the Landscape of Artificial Intelligence Applications against COVID-19
| Autor: | Joseph Bullock, Cynthia Sin Nga Lam, Katherine Hoffmann Pham, Miguel Luengo-Oroz, Alexandra Luccioni |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Social and Information Networks (cs.SI)
FOS: Computer and information sciences Open science Computer Science - Machine Learning Coronavirus disease 2019 (COVID-19) Computer science Computer Science - Artificial Intelligence Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Computer Science - Social and Information Networks 02 engineering and technology Data science World health 3. Good health Machine Learning (cs.LG) Multiple data Computer Science - Computers and Society Artificial Intelligence (cs.AI) Artificial Intelligence Multidisciplinary approach Pandemic Computers and Society (cs.CY) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Applications of artificial intelligence |
| Popis: | COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by the World Health Organization, which has reported over 18 million confirmed cases as of August 5, 2020. In this review, we present an overview of recent studies using Machine Learning and, more broadly, Artificial Intelligence, to tackle many aspects of the COVID-19 crisis. We have identified applications that address challenges posed by COVID-19 at different scales, including: molecular, by identifying new or existing drugs for treatment; clinical, by supporting diagnosis and evaluating prognosis based on medical imaging and non-invasive measures; and societal, by tracking both the epidemic and the accompanying infodemic using multiple data sources. We also review datasets, tools, and resources needed to facilitate Artificial Intelligence research, and discuss strategic considerations related to the operational implementation of multidisciplinary partnerships and open science. We highlight the need for international cooperation to maximize the potential of AI in this and future pandemics. 39 pages, v2: much larger to reflect the significant increase in the size of the body of literature, v3: uploaded with JAIR page numbers and references |
| Databáze: | OpenAIRE |
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