Luo Jianzhao, Yang Ziyu, Xie Yao, He Yang, Wu Miaomiao, Fang Xiang, Liao Xiaoyang
General Practice Ward/International Medical Center Ward, General Practice Medical Center, West China Hospital, Sichuan University, Chengdu, China.
Department of Dermatovenerology, West China Hospital, Sichuan University, Chengdu, China.
Telemed J E Health. 2024 Feb;30(2):393-403. doi: 10.1089/tmj.2023.0101. Epub 2023 Jul 14.
With advances in technology, teledermatology (TD) research has increased. However, an updated comprehensive quantitative analysis of TD research, especially one that identifies emerging trends of TD research in the coronavirus disease 2019 (COVID-19) era, is lacking. To conduct a scientometric analysis of TD research documents between 2002 and 2021 and explore the emerging trends. CiteSpace was used to perform scientometric analysis and yielded visualized network maps with corresponding metric values. Emerging trends were identified mainly through burst detection of keywords/terms, co-cited reference clustering analysis, and structural variability analysis (SVA). A total of 932 documents, containing 27,958 cited references were identified from 2002 to 2021. Most TD research was published in journals from the "Dermatology" and "Health Care Sciences & Services" categories. American, Australian, and European researchers contributed the most research and formed close collaborations. Keywords/terms with strong burst values to date were "primary care," "historical perspective," "emerging technique," "improve access," "mobile teledermoscopy (TDS)," "access," "skin cancer," "telehealth," "recent finding," "artificial intelligence (AI)," "dermatological care," and "dermatological condition." Co-cited reference clustering analysis showed that the recently active cluster labels included "COVID-19 pandemic," "skin cancer," "deep neural network," and "underserved population." The SVA identified two reviews (Tognetti et al. and Mckoy et al.) that may be highly cited in the future. During and after the COVID-19 era, emerging trends in research on TD (especially mobile TDS) may be related to skin cancer and AI as well as further exploration of primary care in underserved areas.
随着技术的进步，远程皮肤病学（TD）研究有所增加。然而，目前缺乏对TD研究的最新全面定量分析，尤其是缺乏能识别2019年冠状病毒病（COVID-19）时代TD研究新趋势的分析。为了对2002年至2021年期间的TD研究文献进行科学计量分析并探索新趋势，我们使用CiteSpace进行科学计量分析，并生成了带有相应指标值的可视化网络图。主要通过关键词/术语的突发检测、共被引参考文献聚类分析和结构变异性分析（SVA）来识别新趋势。2002年至2021年共识别出932篇文献，包含27,958条被引参考文献。大多数TD研究发表在“皮肤病学”和“医疗保健科学与服务”类别的期刊上。美国、澳大利亚和欧洲的研究人员贡献的研究最多，并形成了密切合作。迄今为止具有强烈突发值的关键词/术语有“初级保健”“历史视角”“新兴技术”“改善可及性”“移动远程皮肤镜检查（TDS）”“可及性”“皮肤癌”“远程医疗”“最新发现”“人工智能（AI）”“皮肤病护理”和“皮肤病状况”。共被引参考文献聚类分析表明，最近活跃的聚类标签包括“COVID-19大流行”“皮肤癌”“深度神经网络”和“服务不足人群”。SVA识别出两篇未来可能被高引用的综述（托内蒂等人和麦科伊等人）。在COVID-19时代及之后，TD研究（尤其是移动TDS）的新趋势可能与皮肤癌和人工智能有关，以及对服务不足地区初级保健的进一步探索。
