Artificial intelligence in healthcare business ecosystem: a bibliometric study

Ismail, Albert Feisal @ Muhd Feisal and Mohd Sam, Mohd Fazli and Abu Bakar, Kamarudin and Ahamat, Amiruddin and Adam, Sabrinah and Qureshi, Muhammad Imran (2022) Artificial intelligence in healthcare business ecosystem: a bibliometric study. International Journal Of Online And Biomedical Engineering, 18 (9). pp. 100-114. ISSN 2626-8493

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Abstract

The use of artificial intelligence (AI) in healthcare is rapidly increasing. Digital health start-ups are bringing new digital technologies and services to the market, allowing for cost savings and service improvements in the healthcare sector. However, successful integration of AI into the healthcare ecosystem is required to realise its full potential. A digital ecosystem approach can be used to achieve this integration. Using bibliometric analysis, this research seeks to provide a clear overview of artificial intelligence in the digital healthcare ecosystem by analysing the published literature in the field. A systematic literature search was conducted on an article extracted from the Scopus database related to artificial intelligence in the digital healthcare ecosystem. A search technique was devised in order to collect relevant publications and bibliographic data (e.g., country, research area, sources, and author). The VOS viewer was used to visualise the co-authorship networks of countries as well as the co-occurrence of author keywords (Leiden University). This study is unique in a way that it presents a comprehensive picture of global efforts of the use of artificial intelligence in the healthcare business ecosystem. Academic researchers, policymakers, and healthcare practitioners who wish to collaborate in these areas in the future will benefit from the insights and research directions of this study.

Item Type:	Article
Uncontrolled Keywords:	Artificial intelligence, Healthcare, Business ecosystem, Bibliometric analysis
Divisions:	Faculty of Technology Management and Technopreneurship
Depositing User:	mr eiisaa ahyead
Date Deposited:	24 Mar 2023 11:19
Last Modified:	24 Mar 2023 11:19
URI:	http://eprints.utem.edu.my/id/eprint/26670
Statistic Details:	View Download Statistic

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