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Application of big data and artificial intelligence in epidemic surveillance and containment.
Jiao, Zengtao; Ji, Hanran; Yan, Jun; Qi, Xiaopeng.
Afiliação
  • Jiao Z; AI lab, Yidu Cloud (Beijing) Technology Co., Ltd., Beijing 100083, China.
  • Ji H; Center for Global Public Health, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
  • Yan J; AI lab, Yidu Cloud (Beijing) Technology Co., Ltd., Beijing 100083, China.
  • Qi X; Center for Global Public Health, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Intell Med ; 3(1): 36-43, 2023 Feb.
Article em En | MEDLINE | ID: mdl-36373090
Faced with the current time-sensitive COVID-19 pandemic, the overburdened healthcare systems have resulted in a strong demand to develop newer methods to control the spread of the pandemic. Big data and artificial intelligence (AI) have been leveraged amid the COVID-19 pandemic; however, little is known about their use for supporting public health efforts. In epidemic surveillance and containment, efforts are needed to treat critical patients, track and manage the health status of residents, isolate suspected cases, and develop vaccines and antiviral drugs. The applications of emerging practices of artificial intelligence and big data have become powerful "weapons" to fight against the pandemic and provide strong support in pandemic prevention and control, such as early warning, analysis and judgment, interruption and intervention of epidemic, to achieve goals of early detection, early report, early diagnosis, early isolation and early treatment. These are the decisive factors to control the spread of the epidemic and reduce the mortality. This paper systematically summarized the application of big data and AI in epidemic, and describes practical cases and challenges with emphasis on epidemic prevention and control. The included studies showed that big data and AI have the potential strength to fight against COVID-19. However, many of the proposed methods are not yet widely accepted. Thus, the most rewarding research would be on methods that promise value beyond COVID-19. More efforts are needed for developing standardized reporting protocols or guidelines for practice.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline / Screening_studies Aspecto: Patient_preference Idioma: En Revista: Intell Med Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China País de publicação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline / Screening_studies Aspecto: Patient_preference Idioma: En Revista: Intell Med Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China País de publicação: China