Yuri Silvestre-Barbosa, Vitória Tavares Castro, Larissa Di Carvalho Melo, Paula Elaine Diniz Reis, André Ferreira Leite, Elaine Barros Ferreira, Eliete Neves Silva Guerra
{"title":"Worldwide research trends on artificial intelligence in head and neck cancer: a bibliometric analysis.","authors":"Yuri Silvestre-Barbosa, Vitória Tavares Castro, Larissa Di Carvalho Melo, Paula Elaine Diniz Reis, André Ferreira Leite, Elaine Barros Ferreira, Eliete Neves Silva Guerra","doi":"10.1016/j.oooo.2025.02.014","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>This bibliometric analysis aims to explore scientific data on Artificial Intelligence (AI) and Head and Neck Cancer (HNC).</p><p><strong>Study design: </strong>AI-related HNC articles from the Web of Science Core Collection were searched. VosViewer and Biblioshiny/Bibiometrix for R Studio were used for data synthesis. This analysis covered key characteristics such as sources, authors, affiliations, countries, citations and top cited articles, keyword analysis, and trending topics.</p><p><strong>Results: </strong>A total of 1,019 papers from 1995 to 2024 were included. Among them, 71.6% were original research articles, 7.6% were reviews, and 20.8% took other forms. The fifty most cited documents highlighted radiology as the most explored specialty, with an emphasis on deep learning models for segmentation. The publications have been increasing, with an annual growth rate of 94.4% after 2016. Among the 20 most productive countries, 14 are high-income economies. The keywords of strong citation revealed 2 main clusters: radiomics and radiotherapy. The most frequently keywords include machine learning, deep learning, artificial intelligence, and head and neck cancer, with recent emphasis on diagnosis, survival prediction, and histopathology.</p><p><strong>Conclusions: </strong>There has been an increase in the use of AI in HNC research since 2016 and indicated a notable disparity in publication quantity between high-income and low/middle-income countries. Future research should prioritize clinical validation and standardization to facilitate the integration of AI in HNC management, particularly in underrepresented regions.</p>","PeriodicalId":49010,"journal":{"name":"Oral Surgery Oral Medicine Oral Pathology Oral Radiology","volume":" ","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Oral Surgery Oral Medicine Oral Pathology Oral Radiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.oooo.2025.02.014","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"DENTISTRY, ORAL SURGERY & MEDICINE","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: This bibliometric analysis aims to explore scientific data on Artificial Intelligence (AI) and Head and Neck Cancer (HNC).
Study design: AI-related HNC articles from the Web of Science Core Collection were searched. VosViewer and Biblioshiny/Bibiometrix for R Studio were used for data synthesis. This analysis covered key characteristics such as sources, authors, affiliations, countries, citations and top cited articles, keyword analysis, and trending topics.
Results: A total of 1,019 papers from 1995 to 2024 were included. Among them, 71.6% were original research articles, 7.6% were reviews, and 20.8% took other forms. The fifty most cited documents highlighted radiology as the most explored specialty, with an emphasis on deep learning models for segmentation. The publications have been increasing, with an annual growth rate of 94.4% after 2016. Among the 20 most productive countries, 14 are high-income economies. The keywords of strong citation revealed 2 main clusters: radiomics and radiotherapy. The most frequently keywords include machine learning, deep learning, artificial intelligence, and head and neck cancer, with recent emphasis on diagnosis, survival prediction, and histopathology.
Conclusions: There has been an increase in the use of AI in HNC research since 2016 and indicated a notable disparity in publication quantity between high-income and low/middle-income countries. Future research should prioritize clinical validation and standardization to facilitate the integration of AI in HNC management, particularly in underrepresented regions.
期刊介绍:
Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology is required reading for anyone in the fields of oral surgery, oral medicine, oral pathology, oral radiology or advanced general practice dentistry. It is the only major dental journal that provides a practical and complete overview of the medical and surgical techniques of dental practice in four areas. Topics covered include such current issues as dental implants, treatment of HIV-infected patients, and evaluation and treatment of TMJ disorders. The official publication for nine societies, the Journal is recommended for initial purchase in the Brandon Hill study, Selected List of Books and Journals for the Small Medical Library.