Mapping the landscape of Artificial Intelligence applications against COVID-19

With the continued growth of the COVID-19 pandemic, researchers worldwide are working to better understand, mitigate, and suppress its spread. Key areas of research include studying COVID-19 transmission, facilitating its detection, developing possible vaccines and treatments, and understanding the socio-economic impacts of the pandemic.

In this article, they discuss how Artificial Intelligence can contribute to these goals by enhancing ongoing research efforts, improving the efficiency and speed of existing approaches, and proposing original lines of research. They have conducted an extensive review of the rapidly emerging literature and identified specific applications of AI at three different scales: the molecular scale, including drug discovery-related research; the clinical scale, including individual patient diagnosis and treatment; and the societal scale, including epidemiological and infodemic research. They also review open-source datasets and resources that are available to facilitate the development of AI solutions.

Joseph Bullock,
Alexandra Luccioni,
Katherine Hoffmann Pham,
Cynthia Sin Nga Lam,
Miguel Luengo-Oroz


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