Suppr超能文献

人工智能辅助生物医学出版的最新趋势:定量文献计量分析

Recent Trend in Artificial Intelligence-Assisted Biomedical Publishing: A Quantitative Bibliometric Analysis.

作者信息

Miller Larry E, Bhattacharyya Debjani, Miller Valerie M, Bhattacharyya Mehul

机构信息

Clinical Research, Miller Scientific, Johnson City, USA.

Education, University of Massachusetts Lowell, Lowell, USA.

出版信息

Cureus. 2023 May 19;15(5):e39224. doi: 10.7759/cureus.39224. eCollection 2023 May.

Abstract

The rapid advancements in artificial intelligence (AI) technology in recent years have led to its integration into biomedical publishing. However, the extent to which AI has contributed to developing biomedical literature is unclear. This study aimed to identify trends in AI-generated content within peer-reviewed biomedical literature. We first tested the sensitivity and specificity of commercially available AI-detection software (Originality.AI, Collingwood, Ontario, Canada). Next, we conducted a MEDLINE (Medical Literature Analysis and Retrieval System Online) search to identify randomized controlled trials with available abstracts indexed between January 2020 and March 2023. We randomly selected 30 abstracts per quarter during this period and pasted the abstracts into the AI detection software to determine the probability of AI-generated content. The software yielded 100% sensitivity, 95% specificity, and excellent overall discriminatory ability with an area under the receiving operating curve of 97.6%. Among the 390 MEDLINE-indexed abstracts included in the analysis, the prevalence with a high probability (≥ 90%) of AI-generated text increased during the study period from 21.7% to 36.7% (p=0.01) based on a chi-square test for trend. The increasing prevalence of AI-generated text during the study period was also observed in various sensitivity analyses using AI probability thresholds ranging from 50% to 99% (all p≤0.01). The results of this study suggest that the prevalence of AI-assisted publishing in peer-reviewed journals has been increasing in recent years, even before the widespread adoption of ChatGPT (OpenAI, San Francisco, California, United States) and similar tools. The extent to which natural writing characteristics of the authors, utilization of common AI-powered applications, and introduction of AI elements during the post-acceptance publication phase influence AI detection scores warrants further study.

摘要

近年来,人工智能(AI)技术的快速发展已使其融入生物医学出版领域。然而,人工智能对生物医学文献发展的贡献程度尚不清楚。本研究旨在确定同行评审生物医学文献中人工智能生成内容的趋势。我们首先测试了市售人工智能检测软件(Originality.AI,加拿大安大略省科林伍德)的敏感性和特异性。接下来,我们进行了医学文献数据库(MEDLINE)检索,以识别2020年1月至2023年3月期间索引的有可用摘要的随机对照试验。在此期间,我们每季度随机选择30篇摘要,并将摘要粘贴到人工智能检测软件中,以确定人工智能生成内容的可能性。该软件的敏感性为100%,特异性为95%,总体鉴别能力出色,接受者操作特征曲线下面积为97.6%。在纳入分析的390篇MEDLINE索引摘要中,基于趋势的卡方检验,研究期间人工智能生成文本的高概率(≥90%)患病率从21.7%增加到36.7%(p=0.01)。在使用50%至99%的人工智能概率阈值进行的各种敏感性分析中,也观察到研究期间人工智能生成文本的患病率增加(所有p≤0.01)。本研究结果表明,近年来,即使在ChatGPT(美国加利福尼亚州旧金山的OpenAI)和类似工具广泛应用之前,同行评审期刊中人工智能辅助出版的患病率也一直在上升。作者的自然写作特征、常见人工智能驱动应用的使用以及接受后出版阶段人工智能元素的引入对人工智能检测分数的影响程度值得进一步研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e66/10277011/86b35496ce1b/cureus-0015-00000039224-i01.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验