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An Analysis Review of Detection Coronavirus Disease 2019 (COVID-19) Based on Biosensor Application
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 choice...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7729752/ https://www.ncbi.nlm.nih.gov/pubmed/33256085 http://dx.doi.org/10.3390/s20236764 |
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author | Taha, Bakr Ahmed Al Mashhadany, Yousif Hafiz Mokhtar, Mohd Hadri Dzulkefly Bin Zan, Mohd Saiful Arsad, Norhana |
author_facet | Taha, Bakr Ahmed Al Mashhadany, Yousif Hafiz Mokhtar, Mohd Hadri Dzulkefly Bin Zan, Mohd Saiful Arsad, Norhana |
author_sort | Taha, Bakr Ahmed |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7729752 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-77297522020-12-12 An Analysis Review of Detection Coronavirus Disease 2019 (COVID-19) Based on Biosensor Application Taha, Bakr Ahmed Al Mashhadany, Yousif Hafiz Mokhtar, Mohd Hadri Dzulkefly Bin Zan, Mohd Saiful Arsad, Norhana Sensors (Basel) Review 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. MDPI 2020-11-26 /pmc/articles/PMC7729752/ /pubmed/33256085 http://dx.doi.org/10.3390/s20236764 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Taha, Bakr Ahmed Al Mashhadany, Yousif Hafiz Mokhtar, Mohd Hadri Dzulkefly Bin Zan, Mohd Saiful Arsad, Norhana An Analysis Review of Detection Coronavirus Disease 2019 (COVID-19) Based on Biosensor Application |
title | An Analysis Review of Detection Coronavirus Disease 2019 (COVID-19) Based on Biosensor Application |
title_full | An Analysis Review of Detection Coronavirus Disease 2019 (COVID-19) Based on Biosensor Application |
title_fullStr | An Analysis Review of Detection Coronavirus Disease 2019 (COVID-19) Based on Biosensor Application |
title_full_unstemmed | An Analysis Review of Detection Coronavirus Disease 2019 (COVID-19) Based on Biosensor Application |
title_short | An Analysis Review of Detection Coronavirus Disease 2019 (COVID-19) Based on Biosensor Application |
title_sort | analysis review of detection coronavirus disease 2019 (covid-19) based on biosensor application |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7729752/ https://www.ncbi.nlm.nih.gov/pubmed/33256085 http://dx.doi.org/10.3390/s20236764 |
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