{"title":"识别和可视化医学超声领域人工智能的全球研究趋势和热点：文献计量分析","authors":"Jinting Xiao, Fajuan Shen, Weizhao Lu, Zaiyang Yu, Shengjie Li, Jianlin Wu","doi":"10.2174/0115734056324388240919112351","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Applications of artificial intelligence (AI) in medical ultrasound have rapidly grown in recent years. Therefore, it is necessary to identify and visualize global research trends and hotspots of AI in medical ultrasound to provide guidance for further exploitation.</p><p><strong>Objective: </strong>This study aims to highlight the global research trends and hotspots of the top 100 most-cited papers related to AI in medical ultrasound by combining quantitative and visualization methods.</p><p><strong>Methods: </strong>Articles on AI in medical ultrasound were selected from the WoSCC database and ranked by citation count. After identifying the 100 most-cited papers, we conducted a quantitative and visualized analysis of bibliometric characteristics, including leading research countries, prominent institutions, key authors and journals, author clusters and collaborations, and keyword co-occurrence network analysis.</p><p><strong>Results: </strong>The top 100 highly cited papers from the WoSCC database were published between 1999 and 2021, with total citations ranging from 91 to 1580. The most cited article was published in IEEE Transactions on Medical Imaging. The top three most prolific countries/regions were the United States, mainland China, and the United Kingdom. The most published institutions and journals were Idaho University and IEEE Transactions on Medical Imaging. Twelve authors published more than four papers, with Suri, JS being the most productive author. The most studied topics were \"ultrasound\", \"computer-aided diagnosis\", and \"segmentation\". Ultrasonography of Superficial Organs was the main site that was studied the most.</p><p><strong>Conclusion: </strong>This study provides comprehensive insights into the characteristics of AI in medical ultrasound through quantitative and visualized analysis of the most highly cited literature. It serves as a valuable reference for the development and applications of AI, fostering potential collaborations within this domain.</p>","PeriodicalId":54215,"journal":{"name":"Current Medical Imaging Reviews","volume":" ","pages":"e15734056324388"},"PeriodicalIF":1.1000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identifying and Visualizing Global Research Trends and Hotspots of Artificial Intelligence in Medical Ultrasound: A Bibliometric Analysis.\",\"authors\":\"Jinting Xiao, Fajuan Shen, Weizhao Lu, Zaiyang Yu, Shengjie Li, Jianlin Wu\",\"doi\":\"10.2174/0115734056324388240919112351\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Applications of artificial intelligence (AI) in medical ultrasound have rapidly grown in recent years. Therefore, it is necessary to identify and visualize global research trends and hotspots of AI in medical ultrasound to provide guidance for further exploitation.</p><p><strong>Objective: </strong>This study aims to highlight the global research trends and hotspots of the top 100 most-cited papers related to AI in medical ultrasound by combining quantitative and visualization methods.</p><p><strong>Methods: </strong>Articles on AI in medical ultrasound were selected from the WoSCC database and ranked by citation count. After identifying the 100 most-cited papers, we conducted a quantitative and visualized analysis of bibliometric characteristics, including leading research countries, prominent institutions, key authors and journals, author clusters and collaborations, and keyword co-occurrence network analysis.</p><p><strong>Results: </strong>The top 100 highly cited papers from the WoSCC database were published between 1999 and 2021, with total citations ranging from 91 to 1580. The most cited article was published in IEEE Transactions on Medical Imaging. The top three most prolific countries/regions were the United States, mainland China, and the United Kingdom. The most published institutions and journals were Idaho University and IEEE Transactions on Medical Imaging. Twelve authors published more than four papers, with Suri, JS being the most productive author. The most studied topics were \\\"ultrasound\\\", \\\"computer-aided diagnosis\\\", and \\\"segmentation\\\". Ultrasonography of Superficial Organs was the main site that was studied the most.</p><p><strong>Conclusion: </strong>This study provides comprehensive insights into the characteristics of AI in medical ultrasound through quantitative and visualized analysis of the most highly cited literature. It serves as a valuable reference for the development and applications of AI, fostering potential collaborations within this domain.</p>\",\"PeriodicalId\":54215,\"journal\":{\"name\":\"Current Medical Imaging Reviews\",\"volume\":\" \",\"pages\":\"e15734056324388\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Medical Imaging Reviews\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2174/0115734056324388240919112351\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Medical Imaging Reviews","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2174/0115734056324388240919112351","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Identifying and Visualizing Global Research Trends and Hotspots of Artificial Intelligence in Medical Ultrasound: A Bibliometric Analysis.
Background: Applications of artificial intelligence (AI) in medical ultrasound have rapidly grown in recent years. Therefore, it is necessary to identify and visualize global research trends and hotspots of AI in medical ultrasound to provide guidance for further exploitation.
Objective: This study aims to highlight the global research trends and hotspots of the top 100 most-cited papers related to AI in medical ultrasound by combining quantitative and visualization methods.
Methods: Articles on AI in medical ultrasound were selected from the WoSCC database and ranked by citation count. After identifying the 100 most-cited papers, we conducted a quantitative and visualized analysis of bibliometric characteristics, including leading research countries, prominent institutions, key authors and journals, author clusters and collaborations, and keyword co-occurrence network analysis.
Results: The top 100 highly cited papers from the WoSCC database were published between 1999 and 2021, with total citations ranging from 91 to 1580. The most cited article was published in IEEE Transactions on Medical Imaging. The top three most prolific countries/regions were the United States, mainland China, and the United Kingdom. The most published institutions and journals were Idaho University and IEEE Transactions on Medical Imaging. Twelve authors published more than four papers, with Suri, JS being the most productive author. The most studied topics were "ultrasound", "computer-aided diagnosis", and "segmentation". Ultrasonography of Superficial Organs was the main site that was studied the most.
Conclusion: This study provides comprehensive insights into the characteristics of AI in medical ultrasound through quantitative and visualized analysis of the most highly cited literature. It serves as a valuable reference for the development and applications of AI, fostering potential collaborations within this domain.
期刊介绍：
Current Medical Imaging Reviews publishes frontier review articles, original research articles, drug clinical trial studies and guest edited thematic issues on all the latest advances on medical imaging dedicated to clinical research. All relevant areas are covered by the journal, including advances in the diagnosis, instrumentation and therapeutic applications related to all modern medical imaging techniques.
The journal is essential reading for all clinicians and researchers involved in medical imaging and diagnosis.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
