Abstract
AbstractThis paper provides an early evaluation of Artificial Intelligence (AI) against COVID-19. The main areas where AI can contribute to the fight against COVID-19 are discussed. It is concluded that AI has not yet been impactful against COVID-19. Its use is hampered by a lack of data, and by too much data. Overcoming these constraints will require a careful balance between data privacy and public health, and rigorous human-AI interaction. It is unlikely that these will be addressed in time to be of much help during the present pandemic. In the meantime, extensive gathering of diagnostic data on who is infectious will be essential to save lives, train AI, and limit economic damages.
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Human-Computer Interaction,Philosophy
Reference36 articles.
1. Akhtar M, Kraemer M, Gardner L (2019) A Dynamic neural network model for predicting risk of Zika in real time. BMC Med. https://doi.org/10.1186/s12916-019-1389-3
2. Beck B, Shin B, Choi Y, Park S, Kang K (2020) Predicting commercially available antiviral drugs that may act on the novel coronavirus (2019-nCoV), Wuhan, China through a drug-target interaction deep learning model. bioRxiv. https://doi.org/10.1101/2020.01.31.929547(2 February)
3. Bullock J, Luccioni A, Pham KH, Lam CSN, Luengo-Oroz M (2020) Mapping the landscape of artificial intelligence applications against COVID-19. ArXiv, https://arxiv.org/abs/2003.11336v1
4. Carroll J (2020) Coronavirus outbreak: can machine vision and imaging play a part? Vis Syst Des (19th March)
5. Chen E, Lerman K, Ferrara E (2020a). COVID-19: the first public coronavirus Twitter dataset. ArXiv, https://arxiv.org/abs/2003.07372v1 (16 March)
Cited by
227 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献