在 ChatGPT 成立一周年之际,与医疗保健相关的十大 ChatGPT 出版物的文献计量。

Narra J Pub Date : 2024-08-01 Epub Date: 2024-08-05 DOI:10.52225/narra.v4i2.917
Malik Sallam
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引用次数: 0

摘要

自 2022 年 11 月 30 日公开发布以来,尽管存在道德挑战、隐私问题和可能的偏见,但 ChatGPT 在各种医疗保健应用中显示出了巨大的潜力。本研究的目的是通过文献计量分析,识别和评估 ChatGPT 在医疗保健领域的应用中最具影响力的出版物。本研究在 Scopus、Web of Science 和 Google Scholar 三个数据库中进行了高级检索,以确定 2023 年 11 月 27 日至 30 日期间医疗保健教育、研究和实践中与 ChatGPT 相关的记录。排名基于每个数据库中检索到的引用次数。评估的其他替代指标包括:(1)Semantic Scholar 高影响力引用;(2)PlumX 抓取;(3)PlumX 提及;(4)PlumX 社交媒体;以及(5)Altmetric 关注分数(AAS)。在这三个数据库中共发现了 22 条独特记录,这些记录发表在来自 14 个不同出版商的 17 种不同科学期刊上。在三个数据库的前 10 名中只有两份出版物。发现的出版物类型多种多样,最常见的是社论/评论类出版物(8/22,36.4%)。22 条记录中有 9 条记录的通讯作者隶属于美国的机构(40.9%)。每个数据库的引用次数范围各不相同,其中谷歌学术的引用次数范围最高(1019-121),其次是Scopus(242-88)和Web of Science(171-23)。谷歌学术引文与以下指标有显著相关性:语义学者高影响力引文(斯皮尔曼相关系数ρ=0.840,ppp=0.004)和AASs(ρ=0.542,p=0.009)。总之,尽管存在一些公认的局限性,但这项研究显示了 ChatGPT 在医疗保健领域的应用正在不断发展。当务之急是所有相关利益方采取合作举措,为在医疗保健中以道德、透明和负责任的方式使用 ChatGPT 制定指导方针。该研究揭示了引文与替代指标之间的相关性,强调了其作为衡量出版物影响力的补充工具的实用性,即使在快速发展的研究领域也是如此。
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Bibliometric top ten healthcare-related ChatGPT publications in the first ChatGPT anniversary.

Since its public release on November 30, 2022, ChatGPT has shown promising potential in diverse healthcare applications despite ethical challenges, privacy issues, and possible biases. The aim of this study was to identify and assess the most influential publications in the field of ChatGPT utility in healthcare using bibliometric analysis. The study employed an advanced search on three databases, Scopus, Web of Science, and Google Scholar, to identify ChatGPT-related records in healthcare education, research, and practice between November 27 and 30, 2023. The ranking was based on the retrieved citation count in each database. The additional alternative metrics that were evaluated included (1) Semantic Scholar highly influential citations, (2) PlumX captures, (3) PlumX mentions, (4) PlumX social media and (5) Altmetric Attention Scores (AASs). A total of 22 unique records published in 17 different scientific journals from 14 different publishers were identified in the three databases. Only two publications were in the top 10 list across the three databases. Variable publication types were identified, with the most common being editorial/commentary publications (n=8/22, 36.4%). Nine of the 22 records had corresponding authors affiliated with institutions in the United States (40.9%). The range of citation count varied per database, with the highest range identified in Google Scholar (1019-121), followed by Scopus (242-88), and Web of Science (171-23). Google Scholar citations were correlated significantly with the following metrics: Semantic Scholar highly influential citations (Spearman's correlation coefficient ρ=0.840, p<0.001), PlumX captures (ρ=0.831, p<0.001), PlumX mentions (ρ=0.609, p=0.004), and AASs (ρ=0.542, p=0.009). In conclusion, despite several acknowledged limitations, this study showed the evolving landscape of ChatGPT utility in healthcare. There is an urgent need for collaborative initiatives by all stakeholders involved to establish guidelines for ethical, transparent, and responsible use of ChatGPT in healthcare. The study revealed the correlation between citations and alternative metrics, highlighting its usefulness as a supplement to gauge the impact of publications, even in a rapidly growing research field.

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