Division of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar.
Institute of Digital Healthcare, University of Warwick, Coventry, United Kingdom.
J Med Internet Res. 2020 Dec 15;22(12):e20756. doi: 10.2196/20756.
BACKGROUND: In December 2019, COVID-19 broke out in Wuhan, China, leading to national and international disruptions in health care, business, education, transportation, and nearly every aspect of our daily lives. Artificial intelligence (AI) has been leveraged amid the COVID-19 pandemic; however, little is known about its use for supporting public health efforts. OBJECTIVE: This scoping review aims to explore how AI technology is being used during the COVID-19 pandemic, as reported in the literature. Thus, it is the first review that describes and summarizes features of the identified AI techniques and data sets used for their development and validation. METHODS: A scoping review was conducted following the guidelines of PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews). We searched the most commonly used electronic databases (eg, MEDLINE, EMBASE, and PsycInfo) between April 10 and 12, 2020. These terms were selected based on the target intervention (ie, AI) and the target disease (ie, COVID-19). Two reviewers independently conducted study selection and data extraction. A narrative approach was used to synthesize the extracted data. RESULTS: We considered 82 studies out of the 435 retrieved studies. The most common use of AI was diagnosing COVID-19 cases based on various indicators. AI was also employed in drug and vaccine discovery or repurposing and for assessing their safety. Further, the included studies used AI for forecasting the epidemic development of COVID-19 and predicting its potential hosts and reservoirs. Researchers used AI for patient outcome-related tasks such as assessing the severity of COVID-19, predicting mortality risk, its associated factors, and the length of hospital stay. AI was used for infodemiology to raise awareness to use water, sanitation, and hygiene. The most prominent AI technique used was convolutional neural network, followed by support vector machine. CONCLUSIONS: The included studies showed that AI has the potential to fight against COVID-19. However, many of the proposed methods are not yet clinically accepted. Thus, the most rewarding research will be on methods promising value beyond COVID-19. More efforts are needed for developing standardized reporting protocols or guidelines for studies on AI.
背景：2019 年 12 月，新型冠状病毒肺炎（COVID-19）在中国武汉爆发，导致国内外医疗、商业、教育、交通等领域以及我们日常生活的几乎各个方面都受到干扰。人工智能（AI）在 COVID-19 大流行期间得到了应用；然而，人们对其用于支持公共卫生工作的应用知之甚少。
目的：本范围综述旨在探讨文献中报道的 COVID-19 大流行期间如何使用 AI 技术。因此，这是第一份描述和总结用于其开发和验证的已识别 AI 技术和数据集的特征的综述。
方法：我们按照 PRISMA-ScR（系统评价和荟萃分析扩展的首选报告项目用于范围综述）的指南进行了范围综述。我们于 2020 年 4 月 10 日至 12 日在最常用的电子数据库（例如 MEDLINE、EMBASE 和 PsycInfo）中进行了搜索。这些术语是基于目标干预措施（即 AI）和目标疾病（即 COVID-19）选择的。两名审查员独立进行了研究选择和数据提取。采用叙述方法综合提取的数据。
结果：我们从检索到的 435 项研究中考虑了 82 项研究。AI 的最常见用途是根据各种指标诊断 COVID-19 病例。AI 还用于药物和疫苗的发现或重新利用，并用于评估其安全性。此外，纳入的研究还使用 AI 预测 COVID-19 的流行发展，并预测其潜在宿主和储存库。研究人员使用 AI 进行与患者结局相关的任务，例如评估 COVID-19 的严重程度、预测死亡率、相关因素和住院时间。AI 用于传染病学，以提高对水、卫生和个人卫生的认识。使用最多的 AI 技术是卷积神经网络，其次是支持向量机。
结论：纳入的研究表明 AI 具有对抗 COVID-19 的潜力。然而，许多提出的方法尚未得到临床认可。因此，最有价值的研究将是具有超越 COVID-19 价值的方法。需要进一步努力为 AI 研究制定标准化的报告协议或指南。
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