Robotics & Machine Learning Daily News2024,Issue(Jun.7) :38-39.

Investigators at Henry Ford Hospital Detail Findings in Artificial Intelligence (Application of Artificial Intelligence To Patient-targeted Health Information O n Kidney Stone Disease)

亨利·福特医院的研究人员详细介绍了人工智能的发现(人工智能在肾结石患者健康信息中的应用)

Robotics & Machine Learning Daily News2024,Issue(Jun.7) :38-39.

Investigators at Henry Ford Hospital Detail Findings in Artificial Intelligence (Application of Artificial Intelligence To Patient-targeted Health Information O n Kidney Stone Disease)

亨利·福特医院的研究人员详细介绍了人工智能的发现(人工智能在肾结石患者健康信息中的应用)

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摘要

由一位新闻记者兼机器人与机器学习的新闻编辑每日新闻-关于人工智能的最新研究结果已经发表。根据NewsRx编辑在密歇根州底特律发表的新闻报道,研究表明,“美国医学协会推荐将健康信息写在六年级阅读水平。我们的目标是确定人工智能是否能在肾结石预防和治疗方面优于现有的健康信息。”我们的新闻记者从亨利·福特医院的研究中获得了一句话,“谷歌、必应和雅虎上的‘肾结石预防’和‘肾结石治疗’的前50名搜索结果被选中。重复网页、广告、针对健康专业人士的页面,如科学文章、Video链接、付费订阅页面,等等。”排除与肾结石预防和/或治疗无关的链接。纳入的页面分为学术、医院附属、商业、非营利基金会和其他。使用有效的工具评估网页的质量和可读性。将阅读量与ChatGPT生成的肾结石防治健康信息进行描述性比较,纳入50个肾结石防治网页,49个肾结石治疗网页,阅读量与10~12年级学生相当,质量评定为“FAI R”,无页面评分为“优”,只有20%的学生获得“好”质量。学术、医院附属、商业和非营利基金会出版物的页面之间没有显著差异。ChatGPT评分的文本基因更容易理解,可读性水平低至5年级。现有肾结石疾病信息中使用的语言质量低劣,过于复杂,难以理解。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Artificial In telligence have been published. According to news reporting out of Detroit, Mich igan, by NewsRx editors, research stated, “The American Medical Association reco mmends health information to be written at a 6th grade level reading level. Our aim was to determine whether Artificial Intelligence can outperform the existing health information on kidney stone prevention and treatment.” Our news journalists obtained a quote from the research from Henry Ford Hospital , “The top 50 search results for ‘Kidney Stone Prevention’and ‘Kidney Stone Trea tment’on Google, Bing, and Yahoo were selected. Duplicate webpages, advertisemen ts, pages intended for health professionals such as science articles, links to v ideos, paid subscription pages, and links nonrelated to kidney stone prevention and/or treatment were excluded. Included pages were categorized into academic, h ospital -affiliated, commercial, nonprofit foundations, and other. Quality and r eadability of webpages were evaluated using validated tools, and the reading lev el was descriptively compared with ChatGPT generated health information on kidne y stone prevention and treatment. 50 webpages on kidney stone prevention and 49 on stone treatment were included in this study. The reading level was determined to equate to that of a 10th to 12th grade student. Quality was measured as ‘fai r’with no pages scoring ‘excellent’and only 20% receiving a ‘good’ quality. There was no significant difference between pages from academic, hospit al -affiliated, commercial, and nonprofit foundation publications. The text gene rated by ChatGPT was considerably easier to understand with readability levels m easured as low as 5th grade. The language used in existing information on kidney stone disease is of subpar quality and too complex to understand.”

Key words

Detroit/Michigan/United States/North and Central America/Artificial Intelligence/Emerging Technologies/Hospitals/Machine Learning/Henry Ford Hospital

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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