Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autor principal: Allam, Zaheer
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
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
_version_ 1783562431798181888
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
work_keys_str_mv AT allamzaheer theriseofmachineintelligenceinthecovid19pandemicanditsimpactonhealthpolicy
AT allamzaheer riseofmachineintelligenceinthecovid19pandemicanditsimpactonhealthpolicy