Xing An, Jie Zhou, Qiang Xu, Zhihui Zhao, Weihong Li
{"title":"Artificial intelligence in obstructive sleep apnea: A bibliometric analysis.","authors":"Xing An, Jie Zhou, Qiang Xu, Zhihui Zhao, Weihong Li","doi":"10.1177/20552076251324446","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To conduct a bibliometric analysis using VOSviewer and Citespace to explore the current applications, trends, and future directions of artificial intelligence (AI) in obstructive sleep apnea (OSA).</p><p><strong>Methods: </strong>On 13 September 2024, a computer search was conducted on the Web of Science Core Collection dataset published between 1 January 2011, and 30 August 2024, to identify literature related to the application of AI in OSA. Visualization analysis was performed on countries, institutions, journal sources, authors, co-cited authors, citations, and keywords using Vosviewer and Citespace, and descriptive analysis tables were created by using Microsoft Excel 2021 software.</p><p><strong>Results: </strong>A total of 867 articles were included in this study. The number of publications was low and stable from 2011 to 2016, with a significant increase after 2017. China had the highest number of publications. Alvarez, Daniel, and Hornero, Roberto were the two most prolific authors. Universidad de Valladolid and the IEEE Journal of Biomedical and Health Informatics were the most productive institution and journal, respectively. The top three authors in terms of co-citation frequency are Hassan, Ar, Young, T, and Vicini, C. \"Estimation of the global prevalence and burden of obstructive sleep apnoea: a literature-based analysis\" was cited the most frequently. Keywords such as \"OSA,\" \"machine learning,\" \"Electrocardiography,\" and \"deep learning\" were dominant.</p><p><strong>Conclusion: </strong>AI's application in OSA research is expanding. This study indicates that AI, particularly deep learning, will continue to be a key research area, focusing on diagnosis, identification, personalized treatment, prognosis assessment, telemedicine, and management. Future efforts should enhance international cooperation and interdisciplinary communication to maximize the potential of AI in advancing OSA research, comprehensively empowering sleep health, bringing more precise, convenient, and personalized medical services to patients and ushering in a new era of sleep health.</p>","PeriodicalId":51333,"journal":{"name":"DIGITAL HEALTH","volume":"11 ","pages":"20552076251324446"},"PeriodicalIF":2.9000,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11930495/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"DIGITAL HEALTH","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/20552076251324446","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: To conduct a bibliometric analysis using VOSviewer and Citespace to explore the current applications, trends, and future directions of artificial intelligence (AI) in obstructive sleep apnea (OSA).
Methods: On 13 September 2024, a computer search was conducted on the Web of Science Core Collection dataset published between 1 January 2011, and 30 August 2024, to identify literature related to the application of AI in OSA. Visualization analysis was performed on countries, institutions, journal sources, authors, co-cited authors, citations, and keywords using Vosviewer and Citespace, and descriptive analysis tables were created by using Microsoft Excel 2021 software.
Results: A total of 867 articles were included in this study. The number of publications was low and stable from 2011 to 2016, with a significant increase after 2017. China had the highest number of publications. Alvarez, Daniel, and Hornero, Roberto were the two most prolific authors. Universidad de Valladolid and the IEEE Journal of Biomedical and Health Informatics were the most productive institution and journal, respectively. The top three authors in terms of co-citation frequency are Hassan, Ar, Young, T, and Vicini, C. "Estimation of the global prevalence and burden of obstructive sleep apnoea: a literature-based analysis" was cited the most frequently. Keywords such as "OSA," "machine learning," "Electrocardiography," and "deep learning" were dominant.
Conclusion: AI's application in OSA research is expanding. This study indicates that AI, particularly deep learning, will continue to be a key research area, focusing on diagnosis, identification, personalized treatment, prognosis assessment, telemedicine, and management. Future efforts should enhance international cooperation and interdisciplinary communication to maximize the potential of AI in advancing OSA research, comprehensively empowering sleep health, bringing more precise, convenient, and personalized medical services to patients and ushering in a new era of sleep health.
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