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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...

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Detalles Bibliográficos
Autores principales: Shaikh, Abdul Khalique, Alhashmi, Saadat M, Khalique, Nadia, Khedr, Ahmed M., Raahemifar, Kaamran, Bukhari, Sadaf
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2023
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.
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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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