UKM-Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia.
Department of Electrical Engineering, College of Engineering, University of Anbar, Anbar 00964, Iraq.
Sensors (Basel). 2020 Nov 26;20(23):6764. doi: 10.3390/s20236764.
Timely detection and diagnosis are essentially needed to guide outbreak measures and infection control. It is vital to improve healthcare quality in public places, markets, schools and airports and provide useful insights into the technological environment and help researchers acknowledge the choices and gaps available in this field. In this narrative review, the detection of coronavirus disease 2019 (COVID-19) technologies is summarized and discussed with a comparison between them from several aspects to arrive at an accurate decision on the feasibility of applying the best of these techniques in the biosensors that operate using laser detection technology. The collection of data in this analysis was done by using six reliable academic databases, namely, Science Direct, IEEE Xplore, Scopus, Web of Science, Google Scholar and PubMed. This review includes an analysis review of three highlights: evaluating the hazard of pandemic COVID-19 transmission styles and comparing them with Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) to identify the main causes of the virus spreading, a critical analysis to diagnose coronavirus disease 2019 (COVID-19) based on artificial intelligence using CT scans and CXR images and types of biosensors. Finally, we select the best methods that can potentially stop the propagation of the coronavirus pandemic.
及时的检测和诊断对于指导疫情防控措施至关重要。提高公共场所、市场、学校和机场的医疗质量，并深入了解技术环境，有助于研究人员了解该领域的现有选择和差距。在这篇叙述性综述中，对冠状病毒病 2019（COVID-19）的检测技术进行了总结和讨论，并从多个方面对它们进行了比较，以准确判断使用激光检测技术的生物传感器应用这些技术的最佳技术的可行性。本分析中数据的收集是通过使用六个可靠的学术数据库完成的，即 Science Direct、IEEE Xplore、Scopus、Web of Science、Google Scholar 和 PubMed。本综述包括三个重点的分析综述：评估大流行 COVID-19 传播方式的危害，并将其与严重急性呼吸系统综合征（SARS）和中东呼吸系统综合征（MERS）进行比较，以确定病毒传播的主要原因；使用 CT 扫描和 CXR 图像以及生物传感器类型基于人工智能对冠状病毒病 2019（COVID-19）进行诊断的关键分析；最后，我们选择最有可能阻止冠状病毒大流行传播的最佳方法。
Zotero 插件
