2011-2021 年人工智能在超声医学领域的应用研究进展与热点的文献计量分析。
Research progress and hotspot of the artificial intelligence application in the ultrasound during 2011-2021: A bibliometric analysis.
机构信息
Luodian Clinical Drug Research Center, Shanghai Baoshan Luodian Hospital, Shanghai University, Shanghai, China.
Department of Pancreatic Hepatobiliary Surgery, Changhai Hospital, Naval Medical University, Shanghai, China.
出版信息
Front Public Health. 2022 Sep 15;10:990708. doi: 10.3389/fpubh.2022.990708. eCollection 2022.
Ultrasound, as a common clinical examination tool, inevitably has human errors due to the limitations of manual operation. Artificial intelligence is an advanced computer program that can solve this problem. Therefore, the relevant literature on the application of artificial intelligence in the ultrasonic field from 2011 to 2021 was screened by authors from the Web of Science Core Collection, which aims to summarize the trend of artificial intelligence application in the field of ultrasound, meanwhile, visualize and predict research hotspots. A total of 908 publications were included in the study. Overall, the number of global publications is on the rise, and studies on the application of artificial intelligence in the field of ultrasound continue to increase. China has made the largest contribution in this field. In terms of institutions, Fudan University has the most number of publications. Recently, IEEE Access is the most published journal. Suri J. S. published most of the articles and had the highest number of citations in this field (29 articles). It's worth noting that, convolutional neural networks (CNN), as a kind of deep learning algorithm, was considered to bring better image analysis and processing ability in recent most-cited articles. According to the analysis of keywords, the latest keyword is "COVID-19" (2020.8). The co-occurrence analysis of keywords by VOSviewer visually presented four clusters which consisted of "deep learning," "machine learning," "application in the field of visceral organs," and "application in the field of cardiovascular". The latest hot words of these clusters were "COVID-19; neural-network; hepatocellular carcinoma; atherosclerotic plaques". This study reveals the importance of multi-institutional and multi-field collaboration in promoting research progress.
超声作为一种常见的临床检查工具,由于其手动操作的限制,不可避免地会出现人为错误。人工智能是一种先进的计算机程序,可以解决这个问题。因此,作者从 Web of Science 核心合集筛选了 2011 年至 2021 年关于人工智能在超声领域应用的相关文献,旨在总结人工智能在超声领域应用的趋势,同时可视化和预测研究热点。共纳入 908 篇文献进行研究。总的来说,全球出版物的数量呈上升趋势,人工智能在超声领域的应用研究不断增加。中国在此领域做出了最大的贡献。就机构而言,复旦大学发表的论文数量最多。最近,IEEE Access 是发表论文最多的期刊。Suri J. S. 在该领域发表了最多的文章,并且引用率最高(29 篇)。值得注意的是,卷积神经网络(CNN)作为一种深度学习算法,被认为在最近的高引文章中具有更好的图像分析和处理能力。根据关键词分析,最新的关键词是“COVID-19”(2020.8)。VOSviewer 对关键词的共现分析以四个聚类的形式直观呈现,包括“深度学习”、“机器学习”、“内脏器官领域的应用”和“心血管领域的应用”。这些聚类的最新热门词汇是“COVID-19;神经网络;肝细胞癌;动脉粥样硬化斑块”。本研究揭示了多机构和多领域合作在促进研究进展方面的重要性。
相似文献
Front Biosci (Landmark Ed). 2022-8-31
Comput Methods Programs Biomed. 2023-4
Zhonghua Yan Ke Za Zhi. 2024-2-11
Front Med (Lausanne). 2023-1-12
Quant Imaging Med Surg. 2024-7-1
引用本文的文献
Diagnostics (Basel). 2023-4-20
本文引用的文献
Front Oncol. 2021-7-22
Front Pharmacol. 2021-4-22
Mil Med Res. 2021-1-21
Diagnostics (Basel). 2020-12-6
Cancer Commun (Lond). 2020-4-11
Anaesthesia. 2020-4-28
J Ultrasound Med. 2020-7