Adly Aya Sedky, Adly Afnan Sedky, Adly Mahmoud Sedky
Faculty of Computers and Artificial Intelligence, Helwan University, Cairo, Egypt.
Faculty of Physical Therapy, Cardiovascular-Respiratory Disorders and Geriatrics, Laser Applications in Physical Medicine, Cairo University, Cairo, Egypt.
J Med Internet Res. 2020 Aug 10;22(8):e19104. doi: 10.2196/19104.
Artificial 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.
The 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.
We 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.
Our 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.
We 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.
人工智能（AI）和智能物联网（IIoT）是很有前景的技术，有助于防止冠状病毒病（COVID-19）令人担忧的快速传播，并在疫情期间最大限度地提高安全性。随着COVID-19患者数量呈指数级增长，医生和医护人员很有可能无法治疗所有病例。因此，计算机科学家可以通过引入更智能的解决方案来助力抗击COVID-19，以实现对严重急性呼吸综合征冠状病毒2（SARS-CoV-2，即导致该疾病的病毒）的快速控制。
本综述的目的是分析当前文献，讨论已报道的利用人工智能预防和控制COVID-19的想法的适用性，并全面了解当前系统在特定领域可能如何发挥作用。这可能对全球许多医疗保健管理人员、计算机科学家和政策制定者有很大帮助。
我们在MEDLINE、谷歌学术、Embase和知识网络数据库中对文章进行了电子检索，以形成一篇全面综述，总结最近报道的用于预防和控制COVID-19传播的不同类别的基于人工智能的方法。
我们的检索确定了10种最新的人工智能方法，这些方法被认为能为最大限度提高安全性和防止COVID-19传播提供最佳解决方案。这些方法包括疑似病例检测、大规模筛查、监测、与实验性疗法的交互、肺炎筛查、利用智能物联网进行数据和信息收集与整合、资源分配、预测、建模与模拟以及用于医学隔离的机器人技术。
我们发现关于利用人工智能研究COVID-19与实验性疗法的相互作用、利用人工智能为COVID-19患者进行资源分配，或利用人工智能和智能物联网进行COVID-19数据和信息收集/整合的研究很少或几乎没有。此外，研究人员应进一步强调采用其他方法，包括利用人工智能进行COVID-19预测、利用人工智能进行COVID-19建模与模拟以及利用人工智能机器人进行医学隔离，因为这些重要方法缺乏足够数量的研究。因此，我们建议计算机科学家关注这些仍未得到充分探讨的方法。
