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人工智能在康复科学中的应用:基于 Citespace 的科学计量学研究

Application of Artificial Intelligence in rehabilitation science: A scientometric investigation Utilizing Citespace.

机构信息

College of Physical Education, Huaqiao University, Quanzhou, Fujian 362021, China.

School of Management, Hunan Institute of Engineering, Xiangtan 411104, Hunan, China; Middlesex University, The Burroughs, Hendon, London NW4 4BT, United Kingdom.

出版信息

SLAS Technol. 2024 Aug;29(4):100162. doi: 10.1016/j.slast.2024.100162. Epub 2024 Jul 4.

Abstract

This study presents a scientometric analysis of the intersection between rehabilitation science and artificial intelligence (AI) technologies, using data from the Web of Science (WOS) database from 2002 to 2022. The analysis employed a comprehensive search query with key AI-related terms, focusing on a wide range of publications in rehabilitation science. Utilizing the Citespace tool, the study visualizes and quantifies the relationships between key terms, identifies research trends, and assesses the impact of AI technologies in rehabilitation science. Findings reveal a significant increase in AI-related research in this field, particularly from 2017 onwards, peaking in 2021. The United States has been a leading contributor, followed by countries like England, Australia, Germany, and Canada. Major institutional contributions come from Harvard University and the Pennsylvania Commonwealth System of Higher Education, among others. A keyword co-occurrence network constructed through Citespace identifies nine distinct hot topics and various research frontiers, highlighting evolving focus areas within the field. Burst analysis of keywords indicates a shift from performance and injury-related research to an increasing emphasis on AI and deep learning in recent years. The study also predicts the potential impact of papers, spotlighting works by Kunze KN and others as significantly influencing future research directions. Additionally, it examines the evolution of knowledge bases in AI-related rehabilitation science research, revealing a multidisciplinary core that includes neurology, rehabilitation, and ophthalmology, extending to complementary fields such as medicine and social sciences. This scientometric analysis provides a comprehensive overview of AI's application in rehabilitation science, offering insights into its evolution, impact, and emerging trends over the past two decades. The findings suggest strategic directions for future research, policy-making, and interdisciplinary collaboration in rehabilitation science and AI.

摘要

本研究利用 2002 年至 2022 年期间来自 Web of Science (WOS) 数据库的数据,对康复科学与人工智能 (AI) 技术的交叉进行了科学计量分析。该分析采用了一个全面的搜索查询,其中包含了与 AI 相关的关键术语,重点关注了康复科学领域的广泛出版物。利用 Citespace 工具,该研究可视化并量化了关键词之间的关系,确定了研究趋势,并评估了 AI 技术在康复科学中的影响。研究结果表明,该领域与 AI 相关的研究呈显著增长,特别是自 2017 年以来,在 2021 年达到顶峰。美国一直是主要的贡献者,其次是英国、澳大利亚、德国和加拿大等国家。主要的机构贡献来自哈佛大学和宾夕法尼亚州立高等教育系统等。通过 Citespace 构建的关键词共现网络确定了九个不同的热点和多个研究前沿,突出了该领域内不断演变的重点领域。关键词的突现分析表明,近年来,研究重点从与表现和损伤相关的研究转向越来越强调 AI 和深度学习。该研究还预测了论文的潜在影响,突出了 Kunze KN 等人的作品对未来研究方向的显著影响。此外,它还考察了 AI 相关康复科学研究中知识基础的演变,揭示了一个包括神经病学、康复和眼科学在内的多学科核心,扩展到医学和社会科学等补充领域。这项科学计量分析全面概述了 AI 在康复科学中的应用,提供了对过去二十年中其演变、影响和新兴趋势的深入了解。研究结果为康复科学和 AI 领域的未来研究、决策制定和跨学科合作提供了战略方向。

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