Yang Li, Jian-Lin Wang, Jiao-Jiao Ma, Zhe Sun, Bo Zhang
{"title":"Bibliometric Analysis of Intelligent Ultrasound Imaging in the Diagnosis of Thyroid Nodules.","authors":"Yang Li, Jian-Lin Wang, Jiao-Jiao Ma, Zhe Sun, Bo Zhang","doi":"10.3881/j.issn.1000-503X.16324","DOIUrl":null,"url":null,"abstract":"<p><p>Objective To explore the research progress and hotspots of intelligent ultrasound imaging in the diagnosis of thyroid nodules and clarify the research directions via the bibliometric method.Methods The relevant research articles on intelligent ultrasound imaging in the diagnosis of thyroid nodules were retrieved from the Web of Science Core Collection,covering the period from January 2004 to August 2024.Python was used to analyze the number of annual publications.VOSviewer was used to create the co-occurrence network of authors and the keyword density map.CiteSpace was used to demonstrate the dual-map overlays of the journals,as well as the bursts and clustering of co-citations and keywords.Results A total of 1 179 articles were included.The annual number of publications increased steadily.The involved journals demonstrated high quality,and the publications showed a trend of cross-research.Chinese researchers were the core research force in this field.Haugen et al.'s study on the guidelines for thyroid nodules had the most citations.The clustering of co-citations and keywords indicated studies in multiple fields.Thyroid nodules,cancer,and deep learning were the representative keywords in this field.Conclusions The continuous enrichment of research topics promotes the rapid development of intelligent ultrasound imaging for thyroid nodules.Intelligent diagnosis methods based on deep learning can provide diagnostic suggestions,while there are still challenges such as interpretation.One of the research directions is the deep combination of intelligent diagnosis algorithms and medical knowledge.</p>","PeriodicalId":6919,"journal":{"name":"中国医学科学院学报","volume":"47 4","pages":"590-600"},"PeriodicalIF":0.0000,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"中国医学科学院学报","FirstCategoryId":"1087","ListUrlMain":"https://doi.org/10.3881/j.issn.1000-503X.16324","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
Objective To explore the research progress and hotspots of intelligent ultrasound imaging in the diagnosis of thyroid nodules and clarify the research directions via the bibliometric method.Methods The relevant research articles on intelligent ultrasound imaging in the diagnosis of thyroid nodules were retrieved from the Web of Science Core Collection,covering the period from January 2004 to August 2024.Python was used to analyze the number of annual publications.VOSviewer was used to create the co-occurrence network of authors and the keyword density map.CiteSpace was used to demonstrate the dual-map overlays of the journals,as well as the bursts and clustering of co-citations and keywords.Results A total of 1 179 articles were included.The annual number of publications increased steadily.The involved journals demonstrated high quality,and the publications showed a trend of cross-research.Chinese researchers were the core research force in this field.Haugen et al.'s study on the guidelines for thyroid nodules had the most citations.The clustering of co-citations and keywords indicated studies in multiple fields.Thyroid nodules,cancer,and deep learning were the representative keywords in this field.Conclusions The continuous enrichment of research topics promotes the rapid development of intelligent ultrasound imaging for thyroid nodules.Intelligent diagnosis methods based on deep learning can provide diagnostic suggestions,while there are still challenges such as interpretation.One of the research directions is the deep combination of intelligent diagnosis algorithms and medical knowledge.
期刊介绍:
Acta Academiae Medicinae Sinicae was founded in February 1979. It is a comprehensive medical academic journal published in China and abroad, supervised by the Ministry of Health of the People's Republic of China and sponsored by the Chinese Academy of Medical Sciences and Peking Union Medical College.
The journal mainly reports the latest research results, work progress and dynamics in the fields of basic medicine, clinical medicine, pharmacy, preventive medicine, biomedicine, medical teaching and research, aiming to promote the exchange of medical information and improve the academic level of medicine. At present, the journal has been included in 10 famous foreign retrieval systems and their databases [Medline (PubMed online version), Elsevier, EMBASE, CA, WPRIM, ExtraMED, IC, JST, UPD and EBSCO-ASP]; and has been included in important domestic retrieval systems and databases [China Science Citation Database (Documentation and Information Center of the Chinese Academy of Sciences), China Core Journals Overview (Peking University Library), China Science and Technology Paper Statistical Source Database (China Science and Technology Core Journals) (China Institute of Scientific and Technological Information), China Science and Technology Journal Paper and Citation Database (China Institute of Scientific and Technological Information)].