The outbreak of coronavirus COVID-19 not only brings great disaster to the people of the world, but also brings heavy burden to the medical and health network system. Massive network data traffic and resource optimization requests make traditional network architectures unable to calmly deal with the impact of COVID-19. Artificial intelligence (AI) can effectively raise the upper limit of the medical and health network, as evidenced by the ever-increasing restorative clinical data. In addition, the development of next-generation network (NGN) technologies based on machine learning (ML) has created unlimited possibilities for the emergence of emerging medical methods. In order to reflect the effective results of the current application of AI technologies in the fight against the COVID-19 epidemic and provide a reliable guarantee for subsequent diagnosis and treatment of COVID-19 epidemics, a series of AI technologies which can be used in the diagnosis and treatment of COVID-19 are systematically summarized and analyzed. Based on various AI technologies and methods, we try to propose an AI-based medical network architecture. The architecture uses AI technologies to quickly and effectively realize the monitoring, diagnosis and treatment of patients. Finally, we rationally analyzed the technical challenges and practical problems that may be faced in implementing the architecture. The purpose of this article is to inspire scholars and medical researchers to carry out the latest research in response to the COVID-19 epidemic and make breakthrough medical technology progress.

中文翻译：

---

用于 COVID-19 类流行病的人工智能技术：方法和挑战

冠状病毒COVID-19的爆发不仅给世界人民带来巨大灾难，也给医疗卫生网络系统带来沉重负担。海量的网络数据流量和资源优化请求，使得传统网络架构无法从容应对 COVID-19 的影响。人工智能（AI）可以有效提升医疗健康网络的上限，不断增加的修复性临床数据就是明证。此外，基于机器学习（ML）的下一代网络（NGN）技术的发展，为新兴医疗方法的出现创造了无限可能。为反映当前应用人工智能技术在抗击COVID-19疫情中的有效成果，为后续COVID-19疫情的诊治提供可靠保障，一系列可用于COVID-19疫情的人工智能技术系统总结和分析了 COVID-19 的诊断和治疗。基于各种人工智能技术和方法，我们尝试提出一种基于人工智能的医疗网络架构。该架构采用人工智能技术，快速有效地实现对患者的监测、诊断和治疗。最后，我们理性分析了实现架构可能面临的技术挑战和实际问题。