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Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
Published on: October 24, 2019
Bibliometric analysis for artificial intelligence in the internet of medical things: mapping and performance analysis
Haruna Chiroma1, Ibrahim Abaker Targio Hashem2, Mohammed Maray3
1College of Computer Science and Engineering, University of Hafr Al Batin, Hafar Al Batin, Saudi Arabia.
Abstract:
The development of computer technology has revolutionized how people live and interact in society. The Internet of Things (IoT) has enabled the development of the Internet of Medical Things (IoMT) to transform healthcare delivery. Artificial intelligence has been used to improve the IoMT. Despite the significance of bibliometric analysis in a research area, to the best of the authors' knowledge, based on searches conducted in academic databases, no bibliometric analysis on artificial intelligence (AI) for the IoMT has been conducted. To address this gap, this study proposes performing a comprehensive bibliometric analysis of AI applications in the IoMT. A bibliometric analysis of top literature sources, main disciplines, countries, prolific authors, trending topics, authorship, citations, author-keywords, and co-keywords was conducted. In addition, the structural development of AI in the IoMT highlights its growing popularity. This study found that security and privacy issues are serious concerns hindering the massive adoption of the IoMT. Future research directions on the IoMT, including perspectives on artificial general intelligence, generative artificial intelligence, and explainable artificial intelligence, have been outlined and discussed.
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