Department of Information Technology, Kennesaw State University, Marietta, GA, USA.
Department of Software Engineering and Game Development, Kennesaw State University, Marietta, GA, USA.
J Biomed Inform. 2021 May;117:103751. doi: 10.1016/j.jbi.2021.103751. Epub 2021 Mar 24.
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, 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 perspective. We present a comprehensive survey of the ML algorithms and models that can be used on this expedition and aid with battling the virus.
COVID-19 于 2019 年 12 月首次被发现，并持续在全球各国迅速传播，感染了成千上万的人。该病毒具有致命性，患有既往疾病或年龄超过 60 岁的人死亡风险更高。医药和医疗保健行业已迅速寻求治愈方法，不同的政策已被修订以减轻病毒的传播。虽然机器学习 (ML) 方法已广泛应用于其他领域，但现在迫切需要 ML 辅助诊断系统来进行筛查、跟踪、预测 COVID-19 的传播并寻找针对该病毒的治疗方法。在本文中，我们介绍了 ML 在抗击病毒方面迄今为止所扮演的角色，主要从筛查、预测和疫苗的角度来看待这个问题。我们对可用于这一探索并有助于对抗病毒的 ML 算法和模型进行了全面调查。
