Rehman Amir, Xing Huanlai, Adnan Khan Muhammad, Hussain Mehboob, Hussain Abid, Gulzar Nighat
School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, 611756, China.
Pattern Recognition and Machine Learning, Department of Software, Gachon University, Seongnam 13557, Republic of Korea.
Biomed Signal Process Control. 2023 May;83:104642. doi: 10.1016/j.bspc.2023.104642. Epub 2023 Feb 10.
In light of the constantly changing terrain of the COVID outbreak, medical specialists have implemented proactive schemes for vaccine production. Despite the remarkable COVID-19 vaccine development, the virus has mutated into new variants, including delta and omicron. Currently, the situation is critical in many parts of the world, and precautions are being taken to stop the virus from spreading and mutating. Early identification and diagnosis of COVID-19 are the main challenges faced by emerging technologies during the outbreak. In these circumstances, emerging technologies to tackle Coronavirus have proven magnificent. Artificial intelligence (AI), big data, the internet of medical things (IoMT), robotics, blockchain technology, telemedicine, smart applications, and additive manufacturing are suspicious for detecting, classifying, monitoring, and locating COVID-19. Henceforth, this research aims to glance at these COVID-19 defeating technologies by focusing on their strengths and limitations. A CiteSpace-based bibliometric analysis of the emerging technology was established. The most impactful keywords and the ongoing research frontiers were compiled. Emerging technologies were unstable due to data inconsistency, redundant and noisy datasets, and the inability to aggregate the data due to disparate data formats. Moreover, the privacy and confidentiality of patient medical records are not guaranteed. Hence, Significant data analysis is required to develop an intelligent computational model for effective and quick clinical diagnosis of COVID-19. Remarkably, this article outlines how emerging technology has been used to counteract the virus disaster and offers ongoing research frontiers, directing readers to concentrate on the real challenges and thus facilitating additional explorations to amplify emerging technologies.
鉴于新冠疫情形势不断变化,医学专家已实施了积极的疫苗生产计划。尽管新冠疫苗研发取得了显著成果,但该病毒已变异为包括德尔塔和奥密克戎在内的新变种。目前,世界许多地区的形势严峻,正在采取预防措施以阻止病毒传播和变异。新冠疫情爆发期间,新兴技术面临的主要挑战是对新冠病毒的早期识别和诊断。在这种情况下,应对新冠病毒的新兴技术已被证明非常出色。人工智能(AI)、大数据、医疗物联网(IoMT)、机器人技术、区块链技术、远程医疗、智能应用和增材制造在检测、分类、监测和定位新冠病毒方面值得关注。今后,本研究旨在通过关注这些战胜新冠病毒的技术的优势和局限性来审视它们。建立了基于CiteSpace的新兴技术文献计量分析。汇编了最具影响力的关键词和当前的研究前沿。由于数据不一致、数据集冗余和有噪声,以及由于数据格式不同而无法汇总数据,新兴技术并不稳定。此外,患者病历的隐私和保密性也无法得到保证。因此,需要进行大量数据分析,以开发一种智能计算模型,用于对新冠病毒进行有效、快速的临床诊断。值得注意的是,本文概述了新兴技术如何被用于应对病毒灾难,并提供了当前的研究前沿,引导读者关注实际挑战,从而促进进一步探索以扩大新兴技术的应用。