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Artificial Intelligence and COVID-19: A Multidisciplinary Approach

Overview
Journal Integr Med Res
Publisher Elsevier
Date 2020 Jul 8
PMID 32632356
Citations 34
Authors
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Abstract

The COVID-19 pandemic is taking a colossal toll in human suffering and lives. A significant amount of new scientific research and data sharing is underway due to the pandemic which is still rapidly spreading. There is now a growing amount of coronavirus related datasets as well as published papers that must be leveraged along with artificial intelligence (AI) to fight this pandemic by driving news approaches to drug discovery, vaccine development, and public awareness. AI can be used to mine this avalanche of new data and papers to extract new insights by cross-referencing papers and searching for patterns that AI algorithms could help discover new possible treatments or help in vaccine development. Drug discovery is not a trivial task and AI technologies like deep learning can help accelerate this process by helping predict which existing drugs, or brand-new drug-like molecules could treat COVID-19. AI techniques can also help disseminate vital information across the globe and reduce the spread of false information about COVID-19. The positive power and potential of AI must be harnessed in the fight to slow the spread of COVID-19 in order to save lives and limit the economic havoc due to this horrific disease.

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References
1.
Greer S, Ramo D, Chang Y, Fu M, Moskowitz J, Haritatos J . Use of the Chatbot "Vivibot" to Deliver Positive Psychology Skills and Promote Well-Being Among Young People After Cancer Treatment: Randomized Controlled Feasibility Trial. JMIR Mhealth Uhealth. 2019; 7(10):e15018. PMC: 6913733. DOI: 10.2196/15018. View

2.
Bibault J, Chaix B, Guillemasse A, Cousin S, Escande A, Perrin M . A Chatbot Versus Physicians to Provide Information for Patients With Breast Cancer: Blind, Randomized Controlled Noninferiority Trial. J Med Internet Res. 2019; 21(11):e15787. PMC: 6906616. DOI: 10.2196/15787. View

3.
Alschuler L, Weil A, Horwitz R, Stamets P, Chiasson A, Crocker R . Integrative considerations during the COVID-19 pandemic. Explore (NY). 2020; 16(6):354-356. PMC: 7270871. DOI: 10.1016/j.explore.2020.03.007. View