The COVID-19 global pandemic is a threat not only to the health of millions of individuals, but also to the stability of infrastructure and economies around the world. The disease will inevitably place an overwhelming burden on healthcare systems that cannot be effectively dealt with by existing facilities or responses based on conventional approaches. We believe that a rigorous clinical and societal response can only be mounted by using intelligence derived from a variety of data sources to better utilize scarce healthcare resources, provide personalized patient management plans, inform policy, and expedite clinical trials. In this paper, we introduce five of the most important challenges in responding to COVID-19 and show how each of them can be addressed by recent developments in machine learning (ML) and artificial intelligence (AI). We argue that the integration of these techniques into local, national, and international healthcare systems will save lives, and propose specific methods by which implementation can happen swiftly and efficiently. We offer to extend these resources and knowledge to assist policymakers seeking to implement these techniques.

中文翻译：

---

人工智能和机器学习如何帮助医疗保健系统应对 COVID-19


COVID-19 全球大流行不仅对数百万人的健康构成威胁，而且对世界各地基础设施和经济的稳定构成威胁。这种疾病将不可避免地给医疗保健系统带来巨大负担，而现有设施或基于传统方法的应对措施无法有效应对这一负担。我们相信，只有使用来自各种数据源的情报才能采取严格的临床和社会反应，以更好地利用稀缺的医疗资源，提供个性化的患者管理计划，为政策提供信息并加快临床试验。在本文中，我们介绍了应对 COVID-19 的五个最重要的挑战，并展示了如何通过机器学习 (ML) 和人工智能 (AI) 的最新发展来解决每个挑战。我们认为，将这些技术融入地方、国家和国际医疗保健系统将挽救生命，并提出快速有效实施的具体方法。我们愿意扩展这些资源和知识，以协助寻求实施这些技术的政策制定者。