Letafatkar Negin, El-Sehrawy Amr Ali Mohamed Abdelgawwad, Prasad Kdv, Alkhayyat Ahmad, Amini-Salehi Ehsan, Hasanpour Maryam, Taleshani Masoomeh Namdar, Hashemi Mohammad, Alotaibi Hadi, Rashidian Pegah, Keivanlou Mohammad-Hossein, Hassanipour Soheil
Gastrointestinal and Liver Diseases Research Center, Guilan University of Medical Sciences, Rasht, Iran.
Department of Internal Medicine, Diabetes, Endocrinology and Metabolism, Mansoura University, Mansoura, Egypt.
Front Med (Lausanne). 2025 May 30;12:1532640. doi: 10.3389/fmed.2025.1532640. eCollection 2025.
Artificial intelligence (AI) has revolutionized the field of gastroenterology, particularly in endoscopic and colonoscopic procedures. These AI technologies aim to enhance diagnostic accuracy by facilitating the detection of gastrointestinal lesions, such as polyps and neoplasms. However, the rapid expansion of research in this area necessitates a comprehensive analysis to assess global trends and contributions. This study aims to conduct a thorough bibliometric and visualization analysis of global research focused on AI applications in endoscopy and colonoscopy.
A systematic search was conducted in September 2024 using the Web of Science Core Collection. The data were analyzed using VOSviewer, CiteSpace, and R software, focusing on co-authorship, co-citation, and keyword trends.
Research output on AI in endoscopy and colonoscopy has seen significant growth since 2016, peaking in 2023 with 345 publications. The top contributing country was China, with 399 publications, while the United States led in centrality with a score of 0.27, indicating its key position in research collaborations. Showa University contributed the highest number of institutional publications (64 papers). Mori Y emerged as the leading author, with 53 publications, reflecting his significant influence in the field. The leading journal was Gastrointestinal Endoscopy, contributing 72 publications and accumulating 6,496 citations. The most frequently occurring keywords were "diagnosis," "classification," and "cancer." The cluster analysis identified key research areas, with newer clusters emerging around "adenoma detection," "polyp segmentation," and "wireless capsule endoscopy." These clusters have shown an increasing trend over the past few years, reflecting the growing focus on using AI to optimize diagnostic procedures in real-time.
The bibliometric analysis highlights the rapid expansion and diversification of AI research in endoscopy and colonoscopy. Key clusters, such as "adenoma detection" and "polyp segmentation," underscore the field's shift toward real-time diagnostic improvements. As AI technologies become more integrated into clinical practice, they are set to improve diagnostic accuracy and patient outcomes in gastroenterology.
人工智能（AI）已经彻底改变了胃肠病学领域，尤其是在内镜检查和结肠镜检查程序方面。这些人工智能技术旨在通过促进对胃肠道病变（如息肉和肿瘤）的检测来提高诊断准确性。然而，该领域研究的迅速扩展需要进行全面分析，以评估全球趋势和贡献。本研究旨在对专注于人工智能在内镜检查和结肠镜检查中应用的全球研究进行全面的文献计量和可视化分析。
2024年9月使用科学网核心合集进行了系统检索。使用VOSviewer、CiteSpace和R软件对数据进行分析，重点关注共同作者、共被引和关键词趋势。
自2016年以来，关于人工智能在内镜检查和结肠镜检查方面的研究产出显著增长，在2023年达到峰值，有345篇出版物。贡献最大的国家是中国，有399篇出版物，而美国在中心性方面领先，得分为0.27，表明其在研究合作中的关键地位。昭和大学贡献的机构出版物数量最多（64篇论文）。森Y是主要作者，有53篇出版物，反映了他在该领域的重大影响。领先期刊是《胃肠内镜》，有72篇出版物，累计被引6496次。出现频率最高的关键词是“诊断”“分类”和“癌症”。聚类分析确定了关键研究领域，围绕“腺瘤检测”“息肉分割”和“无线胶囊内镜检查”出现了新的聚类。在过去几年中，这些聚类呈上升趋势，反映出越来越关注使用人工智能实时优化诊断程序。
文献计量分析突出了人工智能在内镜检查和结肠镜检查研究中的迅速扩展和多样化。“腺瘤检测”和“息肉分割”等关键聚类强调了该领域向实时诊断改进的转变。随着人工智能技术更多地融入临床实践，它们必将提高胃肠病学的诊断准确性和患者治疗效果。
