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Approaches Based on Artificial Intelligence and the Internet of Intelligent Things to Prevent the Spread of COVID-19: Scoping Review

机译:基于人工智能和智能事物互联网的方法,以防止Covid-19的传播:范围评论

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摘要

BackgroundArtificial intelligence (AI) and the Internet of Intelligent Things (IIoT) are promising technologies to prevent the concerningly rapid spread of coronavirus disease (COVID-19) and to maximize safety during the pandemic. With the exponential increase in the number of COVID-19 patients, it is highly possible that physicians and health care workers will not be able to treat all cases. Thus, computer scientists can contribute to the fight against COVID-19 by introducing more intelligent solutions to achieve rapid control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes the disease. ObjectiveThe objectives of this review were to analyze the current literature, discuss the applicability of reported ideas for using AI to prevent and control COVID-19, and build a comprehensive view of how current systems may be useful in particular areas. This may be of great help to many health care administrators, computer scientists, and policy makers worldwide. MethodsWe conducted an electronic search of articles in the MEDLINE, Google Scholar, Embase, and Web of Knowledge databases to formulate a comprehensive review that summarizes different categories of the most recently reported AI-based approaches to prevent and control the spread of COVID-19. ResultsOur search identified the 10 most recent AI approaches that were suggested to provide the best solutions for maximizing safety and preventing the spread of COVID-19. These approaches included detection of suspected cases, large-scale screening, monitoring, interactions with experimental therapies, pneumonia screening, use of the IIoT for data and information gathering and integration, resource allocation, predictions, modeling and simulation, and robotics for medical quarantine. ConclusionsWe found few or almost no studies regarding the use of AI to examine COVID-19 interactions with experimental therapies, the use of AI for resource allocation to COVID-19 patients, or the use of AI and the IIoT for COVID-19 data and information gathering/integration. Moreover, the adoption of other approaches, including use of AI for COVID-19 prediction, use of AI for COVID-19 modeling and simulation, and use of AI robotics for medical quarantine, should be further emphasized by researchers because these important approaches lack sufficient numbers of studies. Therefore, we recommend that computer scientists focus on these approaches, which are still not being adequately addressed.
机译:背景技术和智力事物(IIOT)的互联网是有前途的技术,以防止冠状病毒病(Covid-19)的迅速迅速传播并在大流行期间最大化安全性。随着Covid-19患者的数量的指数增加,医生和医疗工作人员将无法治疗所有病例。因此,计算机科学家可以通过引入更聪明的解决方案来实现对严重急性呼吸综合征冠状病毒2(SARS-COV-2)的快速控制,导致疾病的病毒来促进对Covid-19的斗争。本综述目的的目标是分析当前的文献,讨论报告的使用AI预防和控制Covid-19的思想的适用性,并建立了当前系统在特定领域可能有用的综合观点。这对许多医疗管理人员,计算机科学家和全球政策制定者来说可能有很大的帮助。方法网络在Medline,Google Scholar,EMBASE和知识数据库网络中进行了电子搜索,以制定全面的审查,总结了最近报告的基于AI的不同类别,以防止和控制Covid-19的传播。结果评估确定了最近的10个方法,建议为最大化安全性和防止Covid-19传播提供最佳解决方案。这些方法包括检测可疑病例,大规模筛选,监测,与实验疗法的相互作用,肺炎筛查,IIOT用于数据和信息收集,集成,资源分配,预测,建模和仿真,以及医疗检疫的机器人。结论我们发现了关于使用AI检查Covid-19与实验疗法的互动的几乎没有研究,使用AI进行资源分配给Covid-19患者,或使用AI和IIOT进行Covid-19数据和信息收集/集成。此外,研究人员应进一步强调研究人员应该进一步强调使用其他方法,包括用于Covid-19预测的AI对Covid-19预测的使用,以及用于医疗检疫的AI机器人,因为这些重要的方法缺乏足够的方法研究数量。因此,我们建议计算机科学家专注于这些方法,仍未充分解决。

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