Data_Sheet_1_Comparative bibliometric analysis of artificial intelligence-assisted polyp diagnosis and AI-assisted digestive endoscopy: trends and growth in AI gastroenterology (2003–2023).DOCX

IntroductionArtificial intelligence is already widely utilized in gastroenterology. This study aims to comprehensively evaluate the research hotspots and development trends within the field of AI in gastroenterology by employing bibliometric techniques to scrutinize geographical distribution, authorship, affiliated institutions, keyword usage, references, and other pertinent data contained within relevant publications.MethodsThis investigation compiled all pertinent publications related to artificial intelligence in the context of gastrointestinal polyps and digestive endoscopy from 2003 to 2023 within the Web of Science Core Collection database. Furthermore, the study harnessed the tools CiteSpace, VOSviewer, GraphPad Prism and Scimago Graphica for visual data analysis. The study retrieved a total of 2,394 documents in the field of AI in digestive endoscopy and 628 documents specifically related to AI in digestive tract polyps.ResultsThe United States and China are the primary contributors to research in both fields. Since 2019, studies on AI for digestive tract polyps have constituted approximately 25% of the total AI digestive endoscopy studies annually. Six of the top 10 most-cited studies in AI digestive endoscopy also rank among the top 10 most-cited studies in AI for gastrointestinal polyps. Additionally, the number of studies on AI-assisted polyp segmentation is growing the fastest, with significant increases in AI-assisted polyp diagnosis and real-time systems beginning after 2020.DiscussionThe application of AI in gastroenterology has garnered increasing attention. As theoretical advancements in AI for gastroenterology have progressed, real-time diagnosis and detection of gastrointestinal diseases have become feasible in recent years, highlighting the promising potential of AI in this field.

人工智能在胃肠病学领域已被广泛应用。本研究旨在通过运用文献计量学技术，对相关出版物中的地理分布、作者身份、所属机构、关键词使用、参考文献以及其他相关数据进行详尽分析，从而全面评估人工智能在胃肠病学领域的热点研究和发展趋势。方法上，本研究从Web of Science Core Collection数据库中收集了2003年至2023年间与胃肠息肉和消化内镜学相关的所有相关出版物。此外，研究利用CiteSpace、VOSviewer、GraphPad Prism和Scimago Graphica等工具进行可视化数据分析。研究共检索到消化内镜学领域的2,394篇相关文献，以及628篇与消化道息肉相关的AI研究文献。结果显示，美国和中国是这两个领域研究的主要贡献者。自2019年以来，关于消化道息肉的AI研究占总AI消化内镜学研究数量的约25%。在AI消化内镜学领域，排名前10的最受引用研究中，有6项同样位于胃肠息肉AI研究的最受引用研究之列。此外，AI辅助息肉分割的研究数量增长速度最快，AI辅助息肉诊断和实时系统在2020年之后显著增加。讨论中，人工智能在胃肠病学中的应用受到了越来越多的关注。随着人工智能在胃肠病学理论上的进步，近年来实时诊断和检测胃肠道疾病已成为可能，凸显了人工智能在该领域内所蕴含的巨大潜力。