Liu Tao, Rong Yuetong, Li Dan, Zhang Heli, Li Baohua, Cui Guoqing, Shang Shaomei
Peking University School of Nursing, Beijing, China.
Department of Nursing, Peking University Third Hospital, Beijing, China.
Front Med (Lausanne). 2025 Aug 18;12:1624381. doi: 10.3389/fmed.2025.1624381. eCollection 2025.
The fields of dysphagia is progressively acknowledging the transformative capacity of artificial intelligence (AI). The implementation of this technology is profoundly impacting research directions, clinical practices, and healthcare systems. However, existing studies remain scattered and predominantly focus on specific techniques or case applications, lacking a systematic synthesis of global research output, influential contributors, collaboration networks, and evolving thematic trends. A comprehensive bibliometric review is therefore essential to map the current landscape and guide future interdisciplinary research.
This study applies bibliometric and visual analysis methods to comprehensively review the global research activities in AI in dysphagia. Data from 633 articles published by 3,533 authors in 292 journals from January 2000 to February 2025 in Web of Science Core Collection (WoSCC) database were collected and analyzed to identify top publications, sources, authors, institutions, countries/regions, and keywords.
The research activity of AI in dysphagia, which shows an overall upward trend that can be divided into three distinct periods: the first phase (2000-2012), the second phase (2013-2017) and the third phase (2018-Present). The most cited article was Radiotherapy vs. transoral robotic surgery and neck dissection for oropharyngeal squamous cell carcinoma (ORATOR): an open-label, phase 2, randomized trial (344 citations). The most prolific journal was Head and Neck-Journal for the Sciences and Specialties of the Head and Neck with 30 publications. Sejdic Ervin (28 articles), the University of Pittsburgh (39 articles), and the USA (255 articles) were the leading author, institution, and country, respectively. Dysphagia was the most frequently occurring keyword (286 occurrences), while emerging terms included machine learning (ML) and deep learning (DL).
This bibliometric analysis reveals the evolving landscape of AI research in dysphagia, highlighting current hotspots and future directions. AI is driving significant shifts in both research and clinical practice in dysphagia; however, challenges such as interdisciplinary integration and ethical considerations remain to be addressed.
吞咽困难领域日益认识到人工智能（AI）的变革能力。这项技术的应用正在深刻影响研究方向、临床实践和医疗保健系统。然而，现有研究仍然分散，主要集中在特定技术或案例应用上，缺乏对全球研究成果、有影响力的贡献者、合作网络和不断演变的主题趋势的系统综合。因此，全面的文献计量学综述对于描绘当前格局并指导未来的跨学科研究至关重要。
本研究应用文献计量学和可视化分析方法，全面回顾人工智能在吞咽困难领域的全球研究活动。收集并分析了2000年1月至2025年2月期间Web of Science核心合集（WoSCC）数据库中292种期刊上3533位作者发表的633篇文章的数据，以确定顶级出版物、来源、作者、机构、国家/地区和关键词。
人工智能在吞咽困难领域的研究活动总体呈上升趋势，可分为三个不同阶段：第一阶段（2000 - 2012年）、第二阶段（2013 - 2017年）和第三阶段（2018年至今）。被引用次数最多的文章是《放射治疗与经口机器人手术及颈部清扫术治疗口咽鳞状细胞癌（ORATOR）：一项开放标签、2期随机试验》（344次引用）。发文量最多的期刊是《头颈 - 头颈科学与专科杂志》，有30篇出版物。Sejdic Ervin（28篇文章）、匹兹堡大学（39篇文章）和美国（255篇文章）分别是主要作者、机构和国家。吞咽困难是出现频率最高的关键词（出现286次），而新兴术语包括机器学习（ML）和深度学习（DL）。
这项文献计量学分析揭示了人工智能在吞咽困难领域研究的演变格局，突出了当前热点和未来方向。人工智能正在推动吞咽困难领域研究和临床实践的重大转变；然而，跨学科整合和伦理考量等挑战仍有待解决。
