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Artificial intelligence centric scientific research on COVID-19: an analysis based on scientometrics data
With the spread of the deadly coronavirus disease throughout the geographies of the globe, expertise from every field has been sought to fight the impact of the virus. The use of Artificial Intelligence (AI), especially, has been the center of attention due to its capability to produce trustworthy r...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9978294/ https://www.ncbi.nlm.nih.gov/pubmed/37362722 http://dx.doi.org/10.1007/s11042-023-14642-4 |
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author | Shukla, Amit K. Seth, Taniya Muhuri, Pranab K. |
author_facet | Shukla, Amit K. Seth, Taniya Muhuri, Pranab K. |
author_sort | Shukla, Amit K. |
collection | PubMed |
description | With the spread of the deadly coronavirus disease throughout the geographies of the globe, expertise from every field has been sought to fight the impact of the virus. The use of Artificial Intelligence (AI), especially, has been the center of attention due to its capability to produce trustworthy results in a reasonable time. As a result, AI centric based research on coronavirus (or COVID-19) has been receiving growing attention from different domains ranging from medicine, virology, and psychiatry etc. We present this comprehensive study that closely monitors the impact of the pandemic on global research activities related exclusively to AI. In this article, we produce highly informative insights pertaining to publications, such as the best articles, research areas, most productive and influential journals, authors, and institutions. Studies are made on top 50 most cited articles to identify the most influential AI subcategories. We also study the outcome of research from different geographic areas while identifying the research collaborations that have had an impact. This study also compares the outcome of research from the different countries around the globe and produces insights on the same. |
format | Online Article Text |
id | pubmed-9978294 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-99782942023-03-02 Artificial intelligence centric scientific research on COVID-19: an analysis based on scientometrics data Shukla, Amit K. Seth, Taniya Muhuri, Pranab K. Multimed Tools Appl Article With the spread of the deadly coronavirus disease throughout the geographies of the globe, expertise from every field has been sought to fight the impact of the virus. The use of Artificial Intelligence (AI), especially, has been the center of attention due to its capability to produce trustworthy results in a reasonable time. As a result, AI centric based research on coronavirus (or COVID-19) has been receiving growing attention from different domains ranging from medicine, virology, and psychiatry etc. We present this comprehensive study that closely monitors the impact of the pandemic on global research activities related exclusively to AI. In this article, we produce highly informative insights pertaining to publications, such as the best articles, research areas, most productive and influential journals, authors, and institutions. Studies are made on top 50 most cited articles to identify the most influential AI subcategories. We also study the outcome of research from different geographic areas while identifying the research collaborations that have had an impact. This study also compares the outcome of research from the different countries around the globe and produces insights on the same. Springer US 2023-03-02 /pmc/articles/PMC9978294/ /pubmed/37362722 http://dx.doi.org/10.1007/s11042-023-14642-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Shukla, Amit K. Seth, Taniya Muhuri, Pranab K. Artificial intelligence centric scientific research on COVID-19: an analysis based on scientometrics data |
title | Artificial intelligence centric scientific research on COVID-19: an analysis based on scientometrics data |
title_full | Artificial intelligence centric scientific research on COVID-19: an analysis based on scientometrics data |
title_fullStr | Artificial intelligence centric scientific research on COVID-19: an analysis based on scientometrics data |
title_full_unstemmed | Artificial intelligence centric scientific research on COVID-19: an analysis based on scientometrics data |
title_short | Artificial intelligence centric scientific research on COVID-19: an analysis based on scientometrics data |
title_sort | artificial intelligence centric scientific research on covid-19: an analysis based on scientometrics data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9978294/ https://www.ncbi.nlm.nih.gov/pubmed/37362722 http://dx.doi.org/10.1007/s11042-023-14642-4 |
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