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Current Technologies for Detection of COVID-19: Biosensors, Artificial Intelligence and Internet of Medical Things (IoMT): Review
Despite the fact that COVID-19 is no longer a global pandemic due to development and integration of different technologies for the diagnosis and treatment of the disease, technological advancement in the field of molecular biology, electronics, computer science, artificial intelligence, Internet of...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824404/ https://www.ncbi.nlm.nih.gov/pubmed/36617023 http://dx.doi.org/10.3390/s23010426 |
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author | Irkham, Irkham Ibrahim, Abdullahi Umar Nwekwo, Chidi Wilson Al-Turjman, Fadi Hartati, Yeni Wahyuni |
author_facet | Irkham, Irkham Ibrahim, Abdullahi Umar Nwekwo, Chidi Wilson Al-Turjman, Fadi Hartati, Yeni Wahyuni |
author_sort | Irkham, Irkham |
collection | PubMed |
description | Despite the fact that COVID-19 is no longer a global pandemic due to development and integration of different technologies for the diagnosis and treatment of the disease, technological advancement in the field of molecular biology, electronics, computer science, artificial intelligence, Internet of Things, nanotechnology, etc. has led to the development of molecular approaches and computer aided diagnosis for the detection of COVID-19. This study provides a holistic approach on COVID-19 detection based on (1) molecular diagnosis which includes RT-PCR, antigen–antibody, and CRISPR-based biosensors and (2) computer aided detection based on AI-driven models which include deep learning and transfer learning approach. The review also provide comparison between these two emerging technologies and open research issues for the development of smart-IoMT-enabled platforms for the detection of COVID-19. |
format | Online Article Text |
id | pubmed-9824404 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-98244042023-01-08 Current Technologies for Detection of COVID-19: Biosensors, Artificial Intelligence and Internet of Medical Things (IoMT): Review Irkham, Irkham Ibrahim, Abdullahi Umar Nwekwo, Chidi Wilson Al-Turjman, Fadi Hartati, Yeni Wahyuni Sensors (Basel) Review Despite the fact that COVID-19 is no longer a global pandemic due to development and integration of different technologies for the diagnosis and treatment of the disease, technological advancement in the field of molecular biology, electronics, computer science, artificial intelligence, Internet of Things, nanotechnology, etc. has led to the development of molecular approaches and computer aided diagnosis for the detection of COVID-19. This study provides a holistic approach on COVID-19 detection based on (1) molecular diagnosis which includes RT-PCR, antigen–antibody, and CRISPR-based biosensors and (2) computer aided detection based on AI-driven models which include deep learning and transfer learning approach. The review also provide comparison between these two emerging technologies and open research issues for the development of smart-IoMT-enabled platforms for the detection of COVID-19. MDPI 2022-12-30 /pmc/articles/PMC9824404/ /pubmed/36617023 http://dx.doi.org/10.3390/s23010426 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Irkham, Irkham Ibrahim, Abdullahi Umar Nwekwo, Chidi Wilson Al-Turjman, Fadi Hartati, Yeni Wahyuni Current Technologies for Detection of COVID-19: Biosensors, Artificial Intelligence and Internet of Medical Things (IoMT): Review |
title | Current Technologies for Detection of COVID-19: Biosensors, Artificial Intelligence and Internet of Medical Things (IoMT): Review |
title_full | Current Technologies for Detection of COVID-19: Biosensors, Artificial Intelligence and Internet of Medical Things (IoMT): Review |
title_fullStr | Current Technologies for Detection of COVID-19: Biosensors, Artificial Intelligence and Internet of Medical Things (IoMT): Review |
title_full_unstemmed | Current Technologies for Detection of COVID-19: Biosensors, Artificial Intelligence and Internet of Medical Things (IoMT): Review |
title_short | Current Technologies for Detection of COVID-19: Biosensors, Artificial Intelligence and Internet of Medical Things (IoMT): Review |
title_sort | current technologies for detection of covid-19: biosensors, artificial intelligence and internet of medical things (iomt): review |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824404/ https://www.ncbi.nlm.nih.gov/pubmed/36617023 http://dx.doi.org/10.3390/s23010426 |
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