Predictive Classification of Covid-19: Assessing the Impact of Digital Technologies
The recent severe outbreak of the disease has been linked to the COVID-19 virus. It is essential for healthcare professionals and individuals with the capacity to provide intensive care to offer clear explanations of this situation. To address this issue, the World Health Organization (WHO) has impl...
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2-s2.0-85186115937 Kumar B.K.; Majumdar A.; Ismail S.A.; Dixit R.R.; Wahab H.; Ahsan M.H. Predictive Classification of Covid-19: Assessing the Impact of Digital Technologies 2023 7th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2023 - Proceedings 10.1109/ICECA58529.2023.10395103 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186115937&doi=10.1109%2fICECA58529.2023.10395103&partnerID=40&md5=44ec2b573ececd7a3d47b85b9db6d1df The recent severe outbreak of the disease has been linked to the COVID-19 virus. It is essential for healthcare professionals and individuals with the capacity to provide intensive care to offer clear explanations of this situation. To address this issue, the World Health Organization (WHO) has implemented several measures. The National Emergency Telecritical Care Network (NETCCN) has the capability to assess these actions using digital technologies. This section provides a comprehensive explanation of these developments, and NETCCN has put forth a recommendation. Version 2.0 of this digital health data will be made available; it will significantly enhance potential crises in the future. Artificial Intelligence (AI) is used in the suggested digital prediction approach to gather past data on the infection. Telemetry, sophisticated maintenance robotics, and monitoring intelligence may all be found with this technology. These may be created to incorporate data relevant to various infections. Health experts will coordinate all of these. To maintain sustained preparedness for emergency catastrophe protection, frequent testing should be conducted. © 2023 IEEE. Institute of Electrical and Electronics Engineers Inc. English Conference paper |
author |
Kumar B.K.; Majumdar A.; Ismail S.A.; Dixit R.R.; Wahab H.; Ahsan M.H. |
spellingShingle |
Kumar B.K.; Majumdar A.; Ismail S.A.; Dixit R.R.; Wahab H.; Ahsan M.H. Predictive Classification of Covid-19: Assessing the Impact of Digital Technologies |
author_facet |
Kumar B.K.; Majumdar A.; Ismail S.A.; Dixit R.R.; Wahab H.; Ahsan M.H. |
author_sort |
Kumar B.K.; Majumdar A.; Ismail S.A.; Dixit R.R.; Wahab H.; Ahsan M.H. |
title |
Predictive Classification of Covid-19: Assessing the Impact of Digital Technologies |
title_short |
Predictive Classification of Covid-19: Assessing the Impact of Digital Technologies |
title_full |
Predictive Classification of Covid-19: Assessing the Impact of Digital Technologies |
title_fullStr |
Predictive Classification of Covid-19: Assessing the Impact of Digital Technologies |
title_full_unstemmed |
Predictive Classification of Covid-19: Assessing the Impact of Digital Technologies |
title_sort |
Predictive Classification of Covid-19: Assessing the Impact of Digital Technologies |
publishDate |
2023 |
container_title |
7th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2023 - Proceedings |
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doi_str_mv |
10.1109/ICECA58529.2023.10395103 |
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186115937&doi=10.1109%2fICECA58529.2023.10395103&partnerID=40&md5=44ec2b573ececd7a3d47b85b9db6d1df |
description |
The recent severe outbreak of the disease has been linked to the COVID-19 virus. It is essential for healthcare professionals and individuals with the capacity to provide intensive care to offer clear explanations of this situation. To address this issue, the World Health Organization (WHO) has implemented several measures. The National Emergency Telecritical Care Network (NETCCN) has the capability to assess these actions using digital technologies. This section provides a comprehensive explanation of these developments, and NETCCN has put forth a recommendation. Version 2.0 of this digital health data will be made available; it will significantly enhance potential crises in the future. Artificial Intelligence (AI) is used in the suggested digital prediction approach to gather past data on the infection. Telemetry, sophisticated maintenance robotics, and monitoring intelligence may all be found with this technology. These may be created to incorporate data relevant to various infections. Health experts will coordinate all of these. To maintain sustained preparedness for emergency catastrophe protection, frequent testing should be conducted. © 2023 IEEE. |
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Institute of Electrical and Electronics Engineers Inc. |
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English |
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Conference paper |
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Scopus |
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1809677683104153600 |