Emerging technologies for COVID (ET-CoV) detection and diagnosis: Recent advancements, applications, challenges, and future perspectives

• Published in: Biomedical signal processing and control Vol. 83; p. 104642
• Main Authors: Rehman, Amir, Xing, Huanlai, Adnan khan, Muhammad, Hussain, Mehboob, Hussain, Abid, Gulzar, Nighat
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01-05-2023
• Subjects: Bibliometric analysis; CiteSpace; Detection; Emerging technologies; Network visualization; SARS-COVID-2; Network visualization; CiteSpace; Detection; Bibliometric analysis; Emerging technologies; SARS-COVID-2
• ISSN: 1746-8094; 1746-8094
• DOI: 10.1016/j.bspc.2023.104642

[Display omitted]
•The recent emerging-technology applications for the detection of SARS-COVID-2 were discussed.•Specialties were analyzed using CiteSpace bibliometric and network analyses.•The top authors, organizations, co-authors, co-citation, and co-occurrence analyses are highlighted.•Emerging technology-based COVID-19 detection challenges and future perspectives were outlined.
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.