Emerging trends and hotspots in cervical intraepithelial neoplasia research from 2013 to 2023: A bibliometric analysis
Related Experiment Video For Bibliometric analysis
Updated: Jun 23, 2025

Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study
Published on: April 18, 2025
Liya Wang1,2, Bingying Sun1,2, Ji Xu3,4
1The Center for Cervical Disease, The International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200030, China.
Background:
Cervical intraepithelial neoplasia (CIN) encompasses a range of cervical lesions that are closely linked to cervical invasive carcinoma. Early detection and timely treatment of CIN are crucial for preventing the progression of the disease. However, no bibliometric analysis has been conducted in this area. This research aimed to employ bibliometric analysis to summarize the current research hotspots and estimate future research trends in the CIN field.
Methods:
Publications related to CIN (2013-2023) were retrieved from the Science-Citation-Index-Expanded-of-Web-of-Science-Core-Collection. CiteSpace, VOSviewer, and the bibliometric-Online-Analysis-Platform-of-Literature-Metrology were employed to analyze the yearly research output, collaborating institutions or countries, leading researchers, principal journals, co-referenced sources, and emerging keywords.
Results:
In total, 4677 articles on CIN that were published from 2013 to 2023 and met our criteria were extracted. Major publishing platforms were predominantly USA until 2017 when China emerged as the leading source of publications about CIN. The USA was the leading nation in international collaborations. The National-Cancer-Institute (NCI) was the institution with the most publications. Schiffman Mark produced the highest number of articles, with a total of 92. Ten major clusters were identified through co-cited keyword clustering, including prevalence, human papillomavirus, DNA methylation, p16, methylation, conization, HPV genotyping tests (VALGENT), deep learning, vaginal microbiome, and immunohistochemistry. Keyword burst analysis showed that photodynamic therapy and deep learning emerged as prominent research focal points with significant impact in resent three years.
Conclusion:
Global publications on CIN research showed a relatively stable trend over the past eleven years. Current research hotspots are deep learning and photodynamic therapy. This research offered organized data and insightful guidance for future studies, which may help better prevent, screen, and treat CIN.
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