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AIoT Used for COVID-19 Pandemic Prevention and Control.
Chen, Shu-Wen; Gu, Xiao-Wei; Wang, Jia-Ji; Zhu, Hui-Sheng.
Afiliación
  • Chen SW; School of Math and Information Technology, Jiangsu Second Normal University, Nanjing 211200, China.
  • Gu XW; State Key Laboratory of Millimeter Waves, Southeast University, Nanjing 210096, China.
  • Wang JJ; School of Math and Information Technology, Jiangsu Second Normal University, Nanjing 211200, China.
  • Zhu HS; School of Math and Information Technology, Jiangsu Second Normal University, Nanjing 211200, China.
Contrast Media Mol Imaging ; 2021: 3257035, 2021.
Article en En | MEDLINE | ID: mdl-34729056
The pandemic of COVID-19 is continuing to wreak havoc in 2021, with at least 170 million victims around the world. Healthcare systems are overwhelmed by the large-scale virus infection. Luckily, Internet of Things (IoT) is one of the most effective paradigms in the intelligent world, in which the technology of artificial intelligence (AI), like cloud computing and big data analysis, is playing a vital role in preventing the spread of the pandemic of COVID-19. AI and 5G technologies are advancing by leaps and bounds, further strengthening the intelligence and connectivity of IoT applications, and conventional IoT has been gradually upgraded to be more powerful AI + IoT (AIoT). For example, in terms of remote screening and diagnosis of COVID-19 patients, AI technology based on machine learning and deep learning has recently upgraded medical equipment significantly and has reshaped the workflow with minimal contact with patients, so medical specialists can make clinical decisions more efficiently, providing the best protection not only to patients but also to specialists themselves. This paper reviews the latest progress made in combating COVID-19 with both IoT and AI and also provides comprehensive details on how to combat the pandemic of COVID-19 as well as the technologies that may be applied in the future.
Asunto(s)

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Atención a la Salud / Aprendizaje Automático / Internet de las Cosas / SARS-CoV-2 / COVID-19 Tipo de estudio: Prognostic_studies Idioma: En Revista: Contrast Media Mol Imaging Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2021 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Atención a la Salud / Aprendizaje Automático / Internet de las Cosas / SARS-CoV-2 / COVID-19 Tipo de estudio: Prognostic_studies Idioma: En Revista: Contrast Media Mol Imaging Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2021 Tipo del documento: Article