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Bibliometric analysis on the adoption of artificial intelligence applications in the e-health sector
Artificial Intelligent (AI) applications in e-health have evolved considerably in the last 25 years. To track the current research progress in this field, there is a need to analyze the most recent trend of adopting AI applications in e-health. This bibliometric analysis study covers AI applications...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9850136/ https://www.ncbi.nlm.nih.gov/pubmed/36683951 http://dx.doi.org/10.1177/20552076221149296 |
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author | Shaikh, Abdul Khalique Alhashmi, Saadat M Khalique, Nadia Khedr, Ahmed M. Raahemifar, Kaamran Bukhari, Sadaf |
author_facet | Shaikh, Abdul Khalique Alhashmi, Saadat M Khalique, Nadia Khedr, Ahmed M. Raahemifar, Kaamran Bukhari, Sadaf |
author_sort | Shaikh, Abdul Khalique |
collection | PubMed |
description | Artificial Intelligent (AI) applications in e-health have evolved considerably in the last 25 years. To track the current research progress in this field, there is a need to analyze the most recent trend of adopting AI applications in e-health. This bibliometric analysis study covers AI applications in e-health. It differs from the existing literature review as the journal articles are obtained from the Scopus database from its beginning to late 2021 (25 years), which depicts the most recent trend of AI in e-health. The bibliometric analysis is employed to find the statistical and quantitative analysis of available literature of a specific field of study for a particular period. An extensive global literature review is performed to identify the significant research area, authors, or their relationship through published articles. It also provides the researchers with an overview of the work evolution of specific research fields. The study's main contribution highlights the essential authors, journals, institutes, keywords, and states in developing the AI field in e-health. |
format | Online Article Text |
id | pubmed-9850136 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-98501362023-01-20 Bibliometric analysis on the adoption of artificial intelligence applications in the e-health sector Shaikh, Abdul Khalique Alhashmi, Saadat M Khalique, Nadia Khedr, Ahmed M. Raahemifar, Kaamran Bukhari, Sadaf Digit Health Review Article Artificial Intelligent (AI) applications in e-health have evolved considerably in the last 25 years. To track the current research progress in this field, there is a need to analyze the most recent trend of adopting AI applications in e-health. This bibliometric analysis study covers AI applications in e-health. It differs from the existing literature review as the journal articles are obtained from the Scopus database from its beginning to late 2021 (25 years), which depicts the most recent trend of AI in e-health. The bibliometric analysis is employed to find the statistical and quantitative analysis of available literature of a specific field of study for a particular period. An extensive global literature review is performed to identify the significant research area, authors, or their relationship through published articles. It also provides the researchers with an overview of the work evolution of specific research fields. The study's main contribution highlights the essential authors, journals, institutes, keywords, and states in developing the AI field in e-health. SAGE Publications 2023-01-17 /pmc/articles/PMC9850136/ /pubmed/36683951 http://dx.doi.org/10.1177/20552076221149296 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc-nd/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 License (https://creativecommons.org/licenses/by-nc-nd/4.0/) which permits non-commercial use, reproduction and distribution of the work as published without adaptation or alteration, without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Review Article Shaikh, Abdul Khalique Alhashmi, Saadat M Khalique, Nadia Khedr, Ahmed M. Raahemifar, Kaamran Bukhari, Sadaf Bibliometric analysis on the adoption of artificial intelligence applications in the e-health sector |
title | Bibliometric analysis on the adoption of artificial intelligence
applications in the e-health sector |
title_full | Bibliometric analysis on the adoption of artificial intelligence
applications in the e-health sector |
title_fullStr | Bibliometric analysis on the adoption of artificial intelligence
applications in the e-health sector |
title_full_unstemmed | Bibliometric analysis on the adoption of artificial intelligence
applications in the e-health sector |
title_short | Bibliometric analysis on the adoption of artificial intelligence
applications in the e-health sector |
title_sort | bibliometric analysis on the adoption of artificial intelligence
applications in the e-health sector |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9850136/ https://www.ncbi.nlm.nih.gov/pubmed/36683951 http://dx.doi.org/10.1177/20552076221149296 |
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