报告和评估人工智能优于人类医生的道德指南

IF 12.4 1区 医学 Q1 HEALTH CARE SCIENCES & SERVICES NPJ Digital Medicine Pub Date : 2024-10-02 DOI:10.1038/s41746-024-01255-w
Jojanneke Drogt, Megan Milota, Anne van den Brink, Karin Jongsma
{"title":"报告和评估人工智能优于人类医生的道德指南","authors":"Jojanneke Drogt, Megan Milota, Anne van den Brink, Karin Jongsma","doi":"10.1038/s41746-024-01255-w","DOIUrl":null,"url":null,"abstract":"Claims of AI outperforming medical practitioners are under scrutiny, as the evidence supporting many of these claims is not convincing or transparently reported. These claims often lack specificity, contextualization, and empirical grounding. In this comment, we offer constructive ethical guidance that can benefit authors, journal editors, and peer reviewers when reporting and evaluating findings in studies comparing AI to physician performance. The guidance provided here forms an essential addition to current reporting guidelines for healthcare studies using machine learning.","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":null,"pages":null},"PeriodicalIF":12.4000,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41746-024-01255-w.pdf","citationCount":"0","resultStr":"{\"title\":\"Ethical guidance for reporting and evaluating claims of AI outperforming human doctors\",\"authors\":\"Jojanneke Drogt, Megan Milota, Anne van den Brink, Karin Jongsma\",\"doi\":\"10.1038/s41746-024-01255-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Claims of AI outperforming medical practitioners are under scrutiny, as the evidence supporting many of these claims is not convincing or transparently reported. These claims often lack specificity, contextualization, and empirical grounding. In this comment, we offer constructive ethical guidance that can benefit authors, journal editors, and peer reviewers when reporting and evaluating findings in studies comparing AI to physician performance. The guidance provided here forms an essential addition to current reporting guidelines for healthcare studies using machine learning.\",\"PeriodicalId\":19349,\"journal\":{\"name\":\"NPJ Digital Medicine\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":12.4000,\"publicationDate\":\"2024-10-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.nature.com/articles/s41746-024-01255-w.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"NPJ Digital Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.nature.com/articles/s41746-024-01255-w\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"NPJ Digital Medicine","FirstCategoryId":"3","ListUrlMain":"https://www.nature.com/articles/s41746-024-01255-w","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0

摘要

人工智能优于医疗从业人员的说法受到了严格的审查,因为支持其中许多说法的证据并不令人信服,也没有透明的报告。这些说法往往缺乏具体性、背景和实证依据。在本评论中,我们将提供建设性的伦理指导,使作者、期刊编辑和同行评审人员在报告和评估人工智能与医生绩效比较研究结果时受益匪浅。本文提供的指导是对当前使用机器学习的医疗保健研究报告指南的重要补充。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Ethical guidance for reporting and evaluating claims of AI outperforming human doctors
Claims of AI outperforming medical practitioners are under scrutiny, as the evidence supporting many of these claims is not convincing or transparently reported. These claims often lack specificity, contextualization, and empirical grounding. In this comment, we offer constructive ethical guidance that can benefit authors, journal editors, and peer reviewers when reporting and evaluating findings in studies comparing AI to physician performance. The guidance provided here forms an essential addition to current reporting guidelines for healthcare studies using machine learning.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
25.10
自引率
3.30%
发文量
170
审稿时长
15 weeks
期刊介绍: npj Digital Medicine is an online open-access journal that focuses on publishing peer-reviewed research in the field of digital medicine. The journal covers various aspects of digital medicine, including the application and implementation of digital and mobile technologies in clinical settings, virtual healthcare, and the use of artificial intelligence and informatics. The primary goal of the journal is to support innovation and the advancement of healthcare through the integration of new digital and mobile technologies. When determining if a manuscript is suitable for publication, the journal considers four important criteria: novelty, clinical relevance, scientific rigor, and digital innovation.
期刊最新文献
Multisource representation learning for pediatric knowledge extraction from electronic health records The effects of a digital health intervention on patient activation in chronic kidney disease Simulated misuse of large language models and clinical credit systems Accuracy and efficiency of drilling trajectories with augmented reality versus conventional navigation randomized crossover trial Post-marketing surveillance of anticancer drugs using natural language processing of electronic medical records
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1