Artificial intelligence in epidemic management: transforming public health in Brazil and beyond
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References
MacIntyre CR, Lim S, Quigley A. Preventing the next pandemic: use of artificial intelligence for epidemic monitoring and alerts. Cell Rep Med 2022;3(12):100867. http://doi.org/10.1016/j.xcrm.2022.100867. PMid:36543103.
Luengo-Oroz M, Hoffmann Pham K, Bullock J, Kirkpatrick R, Luccioni A, Rubel S, et al. Artificial intelligence cooperation to support the global response to COVID-19. Nat Mach Intell 2020;2(6):295-7. http://doi.org/10.1038/s42256-020-0184-3.
Syrowatka A, Kuznetsova M, Alsubai A, Beckman AL, Bain PA, Craig KJT, et al. Leveraging artificial intelligence for pandemic preparedness and response: a scoping review to identify key use cases. NPJ Digit Med 2021;4(1):96. http://doi.org/10.1038/s41746-021-00459-8. PMid:34112939.
Wang L, Lin ZQ, Wong A. COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images. Sci Rep 2020;10(1):19549. http://doi.org/10.1038/s41598-020-76550-z. PMid:33177550.
Williams CM, Chaturvedi R, Urman RD, Waterman RS, Gabriel RA. Artificial Intelligence and a pandemic: an analysis of the potential uses and drawbacks. J Med Syst 2021;45(3):26. http://doi.org/10.1007/s10916-021-01705-y. PMid:33459840.
Subbiah V. The next generation of evidence-based medicine. Nat Med 2023;29(1):49-58. http://doi.org/10.1038/s41591-022-02160-z. PMid:36646803.
Bragazzi NL, Dai H, Damiani G, Behzadifar M, Martini M, Wu J. How big data and artificial intelligence can help better manage the covid-19 pandemic. Int J Environ Res Public Health 2020;17(9):3176. http://doi.org/10.3390/ijerph17093176. PMid:32370204.
Yoshinari GH Jr, Vitorino LM. How may ChatGPT impact medical teaching? Rev Assoc Med Bras 2023;69(4):e20230282. https://doi.org/10.1590/1806-9282.20230282. PMid:37194805.