论文标题
机器学习研究对抗COVID-19：病毒检测，预防和医疗援助
Machine Learning Research Towards Combating COVID-19: Virus Detection, Spread Prevention, and Medical Assistance
论文作者
论文摘要
Covid-19于2019年12月首次发现，并继续迅速蔓延到全球感染数千和数百万人的国家。该病毒是致命的，患有先前疾病或年龄大于60岁的人的死亡风险更高。医学和医疗保健行业已经急于寻找治愈方法，并且已经修改了不同的政策，以减轻病毒的传播。尽管机器学习（ML）方法已被广泛用于其他领域，但现在对ML辅助诊断系统的需求很高，用于筛选，跟踪和预测Covid-19的传播，并发现对其进行治疗。在本文中，我们介绍了ML到目前为止在对抗病毒中扮演的角色，主要是从筛查，预测和疫苗的角度看待它。我们介绍了可以在此探险中使用的ML算法和模型的全面调查，并协助与病毒作斗争。
COVID-19 was first discovered in December 2019 and has continued to rapidly spread across countries worldwide infecting thousands and millions of people. The virus is deadly, and people who are suffering from prior illnesses or are older than the age of 60 are at a higher risk of mortality. Medicine and Healthcare industries have surged towards finding a cure, and different policies have been amended to mitigate the spread of the virus. While Machine Learning (ML) methods have been widely used in other domains, there is now a high demand for ML-aided diagnosis systems for screening, tracking, and predicting the spread of COVID-19 and finding a cure against it. In this paper, we present a journey of what role ML has played so far in combating the virus, mainly looking at it from a screening, forecasting, and vaccine perspectives. We present a comprehensive survey of the ML algorithms and models that can be used on this expedition and aid with battling the virus.
