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The Rise of Machine Intelligence in the COVID-19 Pandemic and Its Impact on Health Policy
The use of advanced technologies, especially predictive computing in the health sector, is on the rise in this era, and they have successfully transformed the sector with quality insights, better decision-making, and quality policies. Even though notable benefits have been achieved through the uptak...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7378493/ http://dx.doi.org/10.1016/B978-0-12-824313-8.00006-1 |
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author | Allam, Zaheer |
author_facet | Allam, Zaheer |
author_sort | Allam, Zaheer |
collection | PubMed |
description | The use of advanced technologies, especially predictive computing in the health sector, is on the rise in this era, and they have successfully transformed the sector with quality insights, better decision-making, and quality policies. Even though notable benefits have been achieved through the uptake of the technologies, adoption is still slow, as most of them are still new, hence facing some hurdles in their applications especially in national and international policy levels. But the recent case of COVID-19 outbreak has given an opportunity to showcase that these technologies, especially artificial intelligence (AI), have the capacity to produce accurate, real-time, and reliable predictions on issues as serious as pandemic outbreak. A case in point is how companies such as BlueDot and Metabiota managed to correctly predict the spread route of the virus days before such events happened and officially announced by the World Health Organization. In this chapter, an increase in the use of AI-based technologies to detect infectious diseases is underlined and how such uses have led to early detections of infectious diseases. Nevertheless, there is evidence that there is need to enhance data sharing activities, especially by rethinking how to improve the efficiency of data protocols. The chapter further proposes the need for enhanced use of technologies and data sharing to ensure that future outbreaks are detected even earlier, thus accelerating early preventive measures. |
format | Online Article Text |
id | pubmed-7378493 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-73784932020-07-24 The Rise of Machine Intelligence in the COVID-19 Pandemic and Its Impact on Health Policy Allam, Zaheer Surveying the Covid-19 Pandemic and its Implications Article The use of advanced technologies, especially predictive computing in the health sector, is on the rise in this era, and they have successfully transformed the sector with quality insights, better decision-making, and quality policies. Even though notable benefits have been achieved through the uptake of the technologies, adoption is still slow, as most of them are still new, hence facing some hurdles in their applications especially in national and international policy levels. But the recent case of COVID-19 outbreak has given an opportunity to showcase that these technologies, especially artificial intelligence (AI), have the capacity to produce accurate, real-time, and reliable predictions on issues as serious as pandemic outbreak. A case in point is how companies such as BlueDot and Metabiota managed to correctly predict the spread route of the virus days before such events happened and officially announced by the World Health Organization. In this chapter, an increase in the use of AI-based technologies to detect infectious diseases is underlined and how such uses have led to early detections of infectious diseases. Nevertheless, there is evidence that there is need to enhance data sharing activities, especially by rethinking how to improve the efficiency of data protocols. The chapter further proposes the need for enhanced use of technologies and data sharing to ensure that future outbreaks are detected even earlier, thus accelerating early preventive measures. 2020 2020-07-24 /pmc/articles/PMC7378493/ http://dx.doi.org/10.1016/B978-0-12-824313-8.00006-1 Text en Copyright © 2020 Elsevier Inc. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Allam, Zaheer The Rise of Machine Intelligence in the COVID-19 Pandemic and Its Impact on Health Policy |
title | The Rise of Machine Intelligence in the COVID-19 Pandemic and Its Impact on Health Policy |
title_full | The Rise of Machine Intelligence in the COVID-19 Pandemic and Its Impact on Health Policy |
title_fullStr | The Rise of Machine Intelligence in the COVID-19 Pandemic and Its Impact on Health Policy |
title_full_unstemmed | The Rise of Machine Intelligence in the COVID-19 Pandemic and Its Impact on Health Policy |
title_short | The Rise of Machine Intelligence in the COVID-19 Pandemic and Its Impact on Health Policy |
title_sort | rise of machine intelligence in the covid-19 pandemic and its impact on health policy |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7378493/ http://dx.doi.org/10.1016/B978-0-12-824313-8.00006-1 |
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