论文标题
绘制针对COVID-19的人工智能应用的景观
Mapping the Landscape of Artificial Intelligence Applications against COVID-19
论文作者
论文摘要
Covid-19是由SARS-COV-2病毒引起的疾病，已被世界卫生组织宣布为大流行，截至2020年8月5日，该组织报告了超过1800万例确认病例。在这篇综述中，我们介绍了使用机器学习的最新研究概述，并且更广泛地是人工智能，以人工智能，以解决CORVID9 CRISIS的许多方面。我们已经确定了解决Covid-19在不同尺度上提出的挑战的应用，包括：分子，通过识别用于治疗的新药物或现有药物；临床，通过基于医学成像和非侵入性措施来支持诊断并评估预后；和社会，通过使用多个数据源跟踪流行病和随附的流行病。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，并讨论了与多学科合作伙伴关系和开放科学的运营实施相关的战略考虑。我们强调了国际合作的必要性，以最大程度地发挥AI在这一和未来的大流行中的潜力。
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.
