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物联网中人工智能的文献计量分析：图谱绘制与绩效分析

Bibliometric analysis for artificial intelligence in the internet of medical things: mapping and performance analysis.

作者信息

Chiroma Haruna, Hashem Ibrahim Abaker Targio, Maray Mohammed

机构信息

College of Computer Science and Engineering, University of Hafr Al Batin, Hafar Al Batin, Saudi Arabia.

College of Computing and Informatics, Department of Computer Science, University of Sharjah, Sharjah, United Arab Emirates.

出版信息

Front Artif Intell. 2024 Aug 12;7:1347815. doi: 10.3389/frai.2024.1347815. eCollection 2024.

DOI:10.3389/frai.2024.1347815
PMID:39188356
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11345150/
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.

摘要

计算机技术的发展彻底改变了人们在社会中的生活和互动方式。物联网（IoT）推动了医疗物联网（IoMT）的发展，从而改变了医疗服务的提供方式。人工智能已被用于改进IoMT。尽管文献计量分析在一个研究领域具有重要意义，但据作者所知，基于在学术数据库中进行的搜索，尚未对用于IoMT的人工智能（AI）进行文献计量分析。为了填补这一空白，本研究建议对IoMT中的AI应用进行全面的文献计量分析。对顶级文献来源、主要学科、国家、多产作者、热门话题、作者身份、引用、作者关键词和共关键词进行了文献计量分析。此外，IoMT中AI的结构发展凸显了其日益增长的受欢迎程度。本研究发现，安全和隐私问题是阻碍IoMT大规模采用的严重问题。已经概述并讨论了IoMT的未来研究方向，包括关于通用人工智能、生成式人工智能和可解释人工智能的观点。

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