Background: SARS-CoV-2, the unique coronavirus that causes COVID-19, has wreaked damage around the globe, with victims displaying a wide range of difficulties that have encouraged medical professionals to look for innovative technical solutions and therapeutic approaches. Artificial intelligence-based methods have contributed a significant part in tackling complicated issues, and some institutions have been quick to embrace and tailor these solutions in response to the COVID-19 pandemic's obstacles. Here, in this review article, we have covered a few DL techniques for COVID-19 detection and diagnosis, as well as ML techniques for COVID-19 identification, severity classification, vaccine and drug development, mortality rate prediction, contact tracing, risk assessment, and public distancing. This review illustrates the overall impact of AI/ML tools on tackling and managing the outbreak. Purpose: The focus of this research was to undertake a thorough evaluation of the literature on the part of Artificial Intelligence (AI) as a complete and efficient solution in the battle against the COVID-19 epidemic in the domains of detection and diagnostics of disease, mortality prediction and vaccine as well as drug development. Methods: A comprehensive exploration of PubMed, Web of Science, and Science Direct was conducted using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) regulations to find all possibly suitable papers conducted and made publicly available between December 1, 2019, and August 2023. COVID-19, along with AI-specific words, was used to create the query syntax. Results: During the period covered by the search strategy, 961 articles were published and released online. Out of these, a total of 135 papers were chosen for additional investigation. Mortality rate prediction, early detection and diagnosis, vaccine as well as drug development, and lastly, incorporation of AI for supervising and controlling the COVID-19 pandemic were the four main topics focused entirely on AI applications used to tackle the COVID-19 crisis. Out of 135, 60 research papers focused on the detection and diagnosis of the COVID-19 pandemic. Next, 19 of the 135 studies applied a machine-learning approach for mortality rate prediction. Another 22 research publications emphasized the vaccine as well as drug development. Finally, the remaining studies were concentrated on controlling the COVID-19 pandemic by applying AI AI-based approach to it. Conclusion: We compiled papers from the available COVID-19 literature that used AI-based methodologies to impart insights into various COVID-19 topics in this comprehensive study. Our results suggest crucial characteristics, data types, and COVID-19 tools that can aid in medical and translational research facilitation.

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使用基于人工智能 (AI) 的方法应对 COVID-19 危机：系统审查

背景：SARS-CoV-2 是导致 COVID-19 的独特冠状病毒，已在全球范围内造成损害，受害者表现出各种各样的困难，这促使医疗专业人员寻找创新的技术解决方案和治疗方法。基于人工智能的方法在解决复杂问题方面发挥了重要作用，一些机构已迅速接受并定制这些解决方案，以应对 COVID-19 大流行的障碍。在这篇综述文章中，我们介绍了一些用于 COVID-19 检测和诊断的 DL 技术，以及用于 COVID-19 识别、严重程度分类、疫苗和药物开发、死亡率预测、接触者追踪、风险评估的 ML 技术，以及公共距离。这篇综述说明了人工智能/机器学习工具对应对和管理疫情的总体影响。目的：本研究的重点是对有关人工智能 (AI) 的文献进行全面评估，将其作为在疾病检测和诊断领域抗击 COVID-19 流行病的完整而有效的解决方案，死亡率预测和疫苗以及药物开发。方法：使用 PRISMA（系统评价和荟萃分析的首选报告项目）法规对 PubMed、Web of Science 和 Science Direct 进行全面探索，以查找 2019 年 12 月 1 日至 2019 年 12 月 1 日期间发表并公开发表的所有可能合适的论文。 2023 年 8 月。COVID-19 以及 AI 特定单词用于创建查询语法。结果：在检索策略覆盖期间，在线发表和发布了 961 篇文章。其中，总共选择了 135 篇论文进行进一步调查。死亡率预测、早期检测和诊断、疫苗和药物开发以及最后将人工智能纳入监督和控制 COVID-19 大流行是四个主要主题，完全专注于用于应对 COVID-19 危机的人工智能应用。在 135 篇研究论文中，有 60 篇研究论文重点关注了 COVID-19 大流行的检测和诊断。接下来，135 项研究中有 19 项应用机器学习方法来预测死亡率。另外 22 篇研究出版物强调了疫苗和药物开发。最后，剩下的研究集中在通过应用基于人工智能的方法来控制 COVID-19 大流行。结论：我们从现有的 COVID-19 文献中汇编了论文，这些论文使用基于人工智能的方法来深入了解这项综合研究中的各种 COVID-19 主题。我们的结果表明了关键特征、数据类型和 COVID-19 工具，可以帮助促进医学和转化研究。