COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by the World Health Organization, which has reported over 18 million confirmed cases as of August 5, 2020. In this review, we present an overview of recent studies using Machine Learning and, more broadly, Artificial Intelligence, to tackle many aspects of the COVID-19 crisis. We have identified applications that address challenges posed by COVID-19 at different scales, including: molecular, by identifying new or existing drugs for treatment; clinical, by supporting diagnosis and evaluating prognosis based on medical imaging and non-invasive measures; and societal, by tracking both the epidemic and the accompanying infodemic using multiple data sources. We also review datasets, tools, and resources needed to facilitate Artificial Intelligence research, and discuss strategic considerations related to the operational implementation of multidisciplinary partnerships and open science. We highlight the need for international cooperation to maximize the potential of AI in this and future pandemics.
翻译:COVID-19是SARS-CoV-2病毒引起的疾病,世界卫生组织已宣布这一疾病为大流行病,截至2020年8月5日,世界卫生组织已报告1 800多万例确诊病例;在本次审查中,我们概述了最近利用机器学习以及更广义的人工智能进行的研究,以解决COVID-19危机的许多方面;我们查明了应对COVID-19在不同规模上构成的挑战的各种应用,包括:分子,查明新的或现有的治疗用药物;临床,根据医疗成像和非侵入性措施支持诊断和评价预测;社会,利用多种数据来源跟踪该流行病和伴随的无药性;我们还审查了促进人工智能研究所需的数据集、工具和资源,并讨论了与多学科伙伴关系的实际实施和开放科学有关的战略考虑因素;我们强调需要开展国际合作,最大限度地发挥AI在这种和将来的流行病中的潜力。