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<title xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="text"><![CDATA[Domestic and international research status and trend of adolescent myopia: A bibliometrics based analysis]]></title>
<link><![CDATA[http://ies.ijo.cn/gjyke/article/abstract/202309009]]></link>
<description xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="html"><![CDATA[AIM: To explore the current research progress, hot spots and future development trends of myopia in children and adolescents at home and abroad, thus providing references for the further research on the field.METHODS: Using China National Knowledge Infrastructure(CNKI)and Web of Science(WOS)as data sources, the literature on myopia in children and adolescents from January 1, 2003 to December 31, 2022 was collected. Visual analyses were conducted based on the quantity of the published articles, authors, publishing institutions, journals as well as keyword co-occurrence, clustering, timeline graph and emergence by using the VOSviewer and CiteSpace.RESULT: The number of publications on myopia research has increased steadily both articles in Chinese and English. Xian-Gui He and Saw, Seang-Mei have published the most papers, and the Chinese Journal of School Health and Investigative Ophthalmology &#x0026;#x0026; Visual Science published the most related articles. Shanghai Eye Disease Prevention and Treatment Center, and Sun Yat-sen University are the institutions with the most publications in the area. Clinical observation is the main focus of research both domestically and internationally, with orthokeratology, outdoor activities, axial length, prevalence, and influencing factors attracting much attention.CONCLUSION: Current research on myopia in children and adolescents focuses on the epidemiology, intervention measures, and biological parameters of the condition. Future research on myopia epidemiology is likely to become a major focus of research in this area.]]></description>
<pubDate>2023/8/22 13:56:43</pubDate>
<category><![CDATA[Bibliometric  research]]></category>
<author><![CDATA[Si-Yao Wang, Yu Li, Jing Zhang, Yu-Juan Guo, Mei-Mei Zhang, Yue-Hua Zhou]]></author>
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<atom:name>Si-Yao Wang, Yu Li, Jing Zhang, Yu-Juan Guo, Mei-Mei Zhang, Yue-Hua Zhou</atom:name>
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<title xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="text"><![CDATA[Research hotspots and trends of artificial intelligence in diabetic retinopathy based on bibliometrics and high-impact papers]]></title>
<link><![CDATA[http://ies.ijo.cn/gjyke/article/abstract/202311007]]></link>
<description xmlns:cf="http://www.microsoft.com/schemas/rss/core/2005" cf:type="html"><![CDATA[AIM: To analyze research hotspots and trends of artificial intelligence in diabetic retinopathy(DR)based on bibliometrics and high-impact papers.METHODS: Papers on artificial intelligence in DR research published in the Web of Science Core Collection(WoSCC)from January 1, 2012, to December 31, 2022 were retrieved. The data was analyzed by CiteSpace software to examine annual publication number, countries, institutions, source journal, research categories, keywords, and to perform an in-depth analysis of high-impact papers.RESULTS: A total of 1 009 papers on artificial intelligence in DR from 79 countries were included in the study, with 272 papers published in 2022. Notably, China and India contributed 287 and 234 papers, respectively. The United Kingdom exhibited a centrality score of 0.31, while the United States boasted an impressive H-index of 48. Three prominent institutions in the United Kingdom(University of London, Moorfields Eye Hospital, and University College London)and one institution in Egypt(Egyptian Knowledge Bank)all achieved a notable H-index of 14. The primary academic disciplines associated with this research field encompassed ophthalmology, computer science, and artificial intelligence. Burst keywords in the years 2021～2022 included transfer learning, vessel segmentation, and convolutional neural networks.CONCLUSION: China emerged as the leading contributor in terms of publication number in this field, while the United States stood out as a key player. Notably, Egyptian Knowledge Bank and University of London assumed leading roles among research institutions. Additionally, IEEE Access was identified as the most active journal within this domain. The research focus in the field of artificial intelligence in DR has transitioned from AI applications in disease detection and grading to a more concentrated exploration of AI-assisted diagnostic systems. Transfer learning, vessel segmentation, and convolutional neural networks hold substantial promise for widespread applications in this field.]]></description>
<pubDate>2023/10/24 9:37:19</pubDate>
<category><![CDATA[Bibliometric  research]]></category>
<author><![CDATA[Ruo-Yu Wang, Wang-Ting Li, Shao-Chong Zhang, Wei-Hua Yang]]></author>
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<atom:name>Ruo-Yu Wang, Wang-Ting Li, Shao-Chong Zhang, Wei-Hua Yang</atom:name>
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