Lorenzo Storino Ramacciotti, Francesco Cei, Jacob S Hershenhouse, Daniel Mokhtar, Severin Rodler, Karanvir Gill, David Strauss, Luis G Medina, Jie Cai, Andre Luis Abreu, Mihir M Desai, Rene Sotelo, Inderbir S Gill, Giovanni E Cacciamani
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A freeware generative pre-trained transformer (GPT) tool was developed to autogenerate SoMe posts, which included title summarization, key findings, pertinent emojis, hashtags, and digital object identifier links to the article. Three physicians independently evaluated GPT-generated posts for achieving tetrafecta of accuracy and appropriateness criteria. Fifteen scenarios were created from 5 randomly selected posts from each journal. Each scenario contained both the original and the GPT-generated post for the same article. Five questions were formulated to investigate the posts' likability, shareability, engagement, understandability, and comprehensiveness. The paired posts were then randomized and presented to blinded academic authors and general public through Amazon Mechanical Turk (AMT) responders for preference evaluation.</p><p><strong>Results: </strong>Median time for post autogeneration was 10.2 seconds (interquartile range 8.5-12.5). Of the 150 rated GPT-generated posts, 115 (76.6%) met the correctness tetrafecta: 144 (96%) accurately summarized the title, 147 (98%) accurately presented the articles' main findings, 131 (87.3%) appropriately used emojis, and 138 (92%) appropriately used hashtags. A total of 258 academic urologists and 493 AMT responders answered the surveys, wherein the GPT-generated posts consistently outperformed the original journals' posts for both academicians and AMT responders (<i>P</i> < .05).</p><p><strong>Conclusions: </strong>Generative artificial intelligence can automate the creation of SoMe posts from urology journal abstracts that are both accurate and preferable by the academic community and general public.</p>","PeriodicalId":17471,"journal":{"name":"Journal of Urology","volume":" ","pages":"873-881"},"PeriodicalIF":5.9000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Generative Artificial Intelligence Platform for Automating Social Media Posts From Urology Journal Articles: A Cross-Sectional Study and Randomized Assessment.\",\"authors\":\"Lorenzo Storino Ramacciotti, Francesco Cei, Jacob S Hershenhouse, Daniel Mokhtar, Severin Rodler, Karanvir Gill, David Strauss, Luis G Medina, Jie Cai, Andre Luis Abreu, Mihir M Desai, Rene Sotelo, Inderbir S Gill, Giovanni E Cacciamani\",\"doi\":\"10.1097/JU.0000000000004199\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>This cross-sectional study assessed a generative artificial intelligence platform to automate the creation of accurate, appropriate, and compelling social media (SoMe) posts from urological journal articles.</p><p><strong>Materials and methods: </strong>One hundred SoMe posts from the top 3 journals in urology X (formerly Twitter) profiles were collected from August 2022 to October 2023. 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Of the 150 rated GPT-generated posts, 115 (76.6%) met the correctness tetrafecta: 144 (96%) accurately summarized the title, 147 (98%) accurately presented the articles' main findings, 131 (87.3%) appropriately used emojis, and 138 (92%) appropriately used hashtags. 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引用次数: 0
摘要
目的:本横断面研究评估了一个生成式人工智能平台,该平台可根据泌尿外科期刊论文自动创建准确、适当且引人注目的社交媒体(SoMe)帖子:从 2022 年 8 月到 2023 年 10 月,收集了来自泌尿学 X(Twitter)前 3 名期刊的 100 篇 SoMe 帖子。开发了一个免费 GPT 工具,用于自动生成 SoMe 帖子,其中包括标题摘要、主要发现、相关表情符号、标签和文章的 DOI 链接。三位医生对 GPT 生成的帖子进行独立评估,看其是否符合准确性和适当性的四项标准。从每份期刊中随机抽取 5 篇文章,创建了 15 个场景。每个情景都包含同一篇文章的原始帖子和 GPT 生成的帖子。我们设计了五个问题来考察文章的可喜爱性、可分享性、可参与性、可理解性和全面性。然后将配对后的文章进行随机化,并通过亚马逊机械特克(AMT)应答器向盲人学术作者和普通大众展示,以进行偏好评价:帖子自动生成的时间中位数(IQR)为 10.2 秒(8.5-12.5)。在 GPT 生成的 150 篇评分帖子中,115 篇(76.6%)符合正确性四项标准:144 篇(96%)准确概括了标题,147 篇(98%)准确介绍了文章的主要发现,131 篇(87.3%)恰当使用了表情符号和标签 138 篇(92%)。共有 258 名泌尿科学者和 493 名 AMT 答复者回答了调查,其中 GPT 生成的帖子在学者和 AMT 答复者中的表现始终优于原始期刊帖子(P < .05):生成式人工智能可以自动根据泌尿外科期刊摘要创建 SoMe 帖子,这些帖子既准确又受到学术界和公众的青睐。
Generative Artificial Intelligence Platform for Automating Social Media Posts From Urology Journal Articles: A Cross-Sectional Study and Randomized Assessment.
Purpose: This cross-sectional study assessed a generative artificial intelligence platform to automate the creation of accurate, appropriate, and compelling social media (SoMe) posts from urological journal articles.
Materials and methods: One hundred SoMe posts from the top 3 journals in urology X (formerly Twitter) profiles were collected from August 2022 to October 2023. A freeware generative pre-trained transformer (GPT) tool was developed to autogenerate SoMe posts, which included title summarization, key findings, pertinent emojis, hashtags, and digital object identifier links to the article. Three physicians independently evaluated GPT-generated posts for achieving tetrafecta of accuracy and appropriateness criteria. Fifteen scenarios were created from 5 randomly selected posts from each journal. Each scenario contained both the original and the GPT-generated post for the same article. Five questions were formulated to investigate the posts' likability, shareability, engagement, understandability, and comprehensiveness. The paired posts were then randomized and presented to blinded academic authors and general public through Amazon Mechanical Turk (AMT) responders for preference evaluation.
Results: Median time for post autogeneration was 10.2 seconds (interquartile range 8.5-12.5). Of the 150 rated GPT-generated posts, 115 (76.6%) met the correctness tetrafecta: 144 (96%) accurately summarized the title, 147 (98%) accurately presented the articles' main findings, 131 (87.3%) appropriately used emojis, and 138 (92%) appropriately used hashtags. A total of 258 academic urologists and 493 AMT responders answered the surveys, wherein the GPT-generated posts consistently outperformed the original journals' posts for both academicians and AMT responders (P < .05).
Conclusions: Generative artificial intelligence can automate the creation of SoMe posts from urology journal abstracts that are both accurate and preferable by the academic community and general public.
期刊介绍:
The Official Journal of the American Urological Association (AUA), and the most widely read and highly cited journal in the field, The Journal of Urology® brings solid coverage of the clinically relevant content needed to stay at the forefront of the dynamic field of urology. This premier journal presents investigative studies on critical areas of research and practice, survey articles providing short condensations of the best and most important urology literature worldwide, and practice-oriented reports on significant clinical observations.