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A Study on Fight Against COVID-19 from Latest Technological Intervention

Uncontrolled spread of pandemic COVID-19 in India and across the globe over several months, created an impact as never before any pandemic would have created. This certainly demands a technological intervention from all possibility to overcome the situation and lead a normal life as early as possibl...

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Detalles Bibliográficos
Autores principales: Arulprakash, Enoch, Aruldoss, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Singapore 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7437103/
https://www.ncbi.nlm.nih.gov/pubmed/33063054
http://dx.doi.org/10.1007/s42979-020-00301-0
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author Arulprakash, Enoch
Aruldoss, Martin
author_facet Arulprakash, Enoch
Aruldoss, Martin
author_sort Arulprakash, Enoch
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description Uncontrolled spread of pandemic COVID-19 in India and across the globe over several months, created an impact as never before any pandemic would have created. This certainly demands a technological intervention from all possibility to overcome the situation and lead a normal life as early as possible. AI/Machine learning responds to the situation, through inspecting different aspects of the pandemic. This paper analyses and studies those aspects, (I) Quarantine and statistical aspect: Quarantine potentially affected candidates (person who is in touch, travel history) through Data analytics/Machine learning. (II) Diagnosis and Treatment aspect: Early detection and fast treatment will save lives. Diagnosis using deep learning assists radiologist from saving their effort and time to a greater extent and arrives faster conclusion. (III) Prevention aspect: Monitoring and enforce social distancing through visual social distancing using deep learning and Computer vision.
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spelling pubmed-74371032020-08-19 A Study on Fight Against COVID-19 from Latest Technological Intervention Arulprakash, Enoch Aruldoss, Martin SN Comput Sci Review Article Uncontrolled spread of pandemic COVID-19 in India and across the globe over several months, created an impact as never before any pandemic would have created. This certainly demands a technological intervention from all possibility to overcome the situation and lead a normal life as early as possible. AI/Machine learning responds to the situation, through inspecting different aspects of the pandemic. This paper analyses and studies those aspects, (I) Quarantine and statistical aspect: Quarantine potentially affected candidates (person who is in touch, travel history) through Data analytics/Machine learning. (II) Diagnosis and Treatment aspect: Early detection and fast treatment will save lives. Diagnosis using deep learning assists radiologist from saving their effort and time to a greater extent and arrives faster conclusion. (III) Prevention aspect: Monitoring and enforce social distancing through visual social distancing using deep learning and Computer vision. Springer Singapore 2020-08-19 2020 /pmc/articles/PMC7437103/ /pubmed/33063054 http://dx.doi.org/10.1007/s42979-020-00301-0 Text en © Springer Nature Singapore Pte Ltd 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Review Article
Arulprakash, Enoch
Aruldoss, Martin
A Study on Fight Against COVID-19 from Latest Technological Intervention
title A Study on Fight Against COVID-19 from Latest Technological Intervention
title_full A Study on Fight Against COVID-19 from Latest Technological Intervention
title_fullStr A Study on Fight Against COVID-19 from Latest Technological Intervention
title_full_unstemmed A Study on Fight Against COVID-19 from Latest Technological Intervention
title_short A Study on Fight Against COVID-19 from Latest Technological Intervention
title_sort study on fight against covid-19 from latest technological intervention
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7437103/
https://www.ncbi.nlm.nih.gov/pubmed/33063054
http://dx.doi.org/10.1007/s42979-020-00301-0
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