摘要：
目的 识别医学领域因计算机辅助或生成内容撤稿特征，为防范学术不端、维护学术诚信提出建议。 方法 收集撤稿观察数据库中的1743篇因计算机辅助或生成内容引发撤稿的文章，从年份分布与撤稿时滞、作者及来源国家、学科特点、期刊及出版商分布等角度总结其撤稿特征。 结果 2022年是计算机辅助或生成内容撤稿文章的发表高峰，2023年是因计算机辅助或生成内容撤稿文章数量最多的一年。平均撤稿时滞为545.08 d；1743篇文章共涉及作者8372位，来自66个国家，中国被撤回文章最多；纯医学类文章共涉及30个医学类学科，心血管病学占比最大，主要与生物学、技术、遗传学3大类非医学学科交叉；期刊发文规模与撤稿量之间无线性关联，撤稿文章多集中在Journal of Healthcare Engineering期刊和 Hindawi出版商。 结论 建议技术赋能期刊筛查，提高期刊初审质量；提升科研人员认知规范，树立科研诚信理念；加强编辑间的合作，实现跨学科编辑团队与审核标准的协同创新。
关键词:
医学领域,
撤稿,
计算机辅助内容,
计算机生成内容,
学术诚信
Abstract:
Purposes Identify retraction characteristics in the medical field due to computer-aided or computer-generated content， and propose suggestions to prevent academic misconduct and maintain academic integrity. Methods A total of 1743 articles retracted due to computer-assisted or generated content were collected from the Retraction Watch database， summarizing their retraction characteristics from perspectives such as time distribution and retraction delays， authors and countries of origin， disciplinary characteristics， and distribution of journals and publishers. Findings The year 2022 marked the peak for the publication of retracted articles involving computer-aided or computer-generated content， while 2023 saw the highest number of retractions for such content；the average retraction delay was 545.08 d； the 1743 articles involved 8372 authors from 66 countries， with China having the highest number of retracted articles； pure medical articles involved 30 medical disciplines， with cardiology accounting for the largest proportion， mainly intersecting with three non-medical disciplines： biology， technology， and genetics； there was no linear correlation between the scale of journal publications and the volume of retractions， with many retracted articles concentrated in the Journal of Healthcare Engineering and published by Hindawi. Conclusions Leverage technology to empower journal screening and improve the quality of preliminary journal review； enhance researchers’ understanding of standards and establish the concept of research integrity； strengthen collaboration among editors to achieve synergistic innovation between interdisciplinary editorial teams and review standards.
Key words:
Medical field,
Retraction,
Computer-aided content,
Computer-generated content,
Academic integrity
李亚萍, 李楚威, 丁佐奇. 医学领域计算机辅助或生成内容撤稿文章的特征[J]. 中国科技期刊研究, 2025, 36(12): 1791-1799.
LI Yaping, LI Chuwei, DING Zuoqi. Characteristics of retracted articles with computer⁃aided or computer⁃generated content in the medical field[J]. Chinese Journal of Scientific and Technical Periodicals, 2025, 36(12): 1791-1799.