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Erschienen in: Journal of Medical Systems 3/2021

01.03.2021 | Editorial

Artificial Intelligence and a Pandemic: an Analysis of the Potential Uses and Drawbacks

verfasst von: Christina M. Williams, Rahul Chaturvedi, Richard D. Urman, Ruth S. Waterman, Rodney A. Gabriel

Erschienen in: Journal of Medical Systems | Ausgabe 3/2021

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Excerpt

Pandemics pose unique challenges in that their rapid spread necessitates a quick response on many fronts, from diagnostic modalities to drug development and medical resource allocation and planning. Quarantines that are necessarily implemented, as seen with the coronavirus disease-2019 (COVID-19) outbreak, further strain these efforts, as a result of hospital personnel and researchers potentially being furloughed while being evaluated for symptoms themselves [1]. Not only is the potential lack of staff detrimental to those who have the disease in question, but also to others who may require access to the emergency department or intensive care. Artificial intelligence (AI) methodologies have increasingly been studied as a potential tool to aid in improving existing modalities. The number of research papers being published on COVID-19 and AI have been growing exponentially since March of 2020 [2]. However, while AI has shown immense promise in its ability to help counter the rapid spread of disease in a pandemic, there are significant potential ethical and legal considerations that must be taken into account before it can be used on a widespread scale. …
Literatur
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Zurück zum Zitat Bullock, J., Luccioni, A., Pham, K.H., Lam, C.S.N., Luengo-Oroz, M., Mapping the landscape of artificial intelligence applications against COVID-19. ArXiv:arXiv:2003.11336, 2020. Bullock, J., Luccioni, A., Pham, K.H., Lam, C.S.N., Luengo-Oroz, M., Mapping the landscape of artificial intelligence applications against COVID-19. ArXiv:arXiv:2003.11336, 2020.
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Zurück zum Zitat Wang, L., Wong, A., COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 Cases from Chest X-Ray Images. ArXiv:arXiv:2003.09871, n.d. Wang, L., Wong, A., COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 Cases from Chest X-Ray Images. ArXiv:arXiv:2003.09871, n.d.
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Zurück zum Zitat Scott, I.A., Coiera, E.W., Can AI help in the fight against COVID-19? Med J Aust, 2020. Scott, I.A., Coiera, E.W., Can AI help in the fight against COVID-19? Med J Aust, 2020.
Metadaten
Titel
Artificial Intelligence and a Pandemic: an Analysis of the Potential Uses and Drawbacks
verfasst von
Christina M. Williams
Rahul Chaturvedi
Richard D. Urman
Ruth S. Waterman
Rodney A. Gabriel
Publikationsdatum
01.03.2021
Verlag
Springer US
Erschienen in
Journal of Medical Systems / Ausgabe 3/2021
Print ISSN: 0148-5598
Elektronische ISSN: 1573-689X
DOI
https://doi.org/10.1007/s10916-021-01705-y

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