GDPR

GDPR
  • 文章类型: Journal Article
    背景:随着AI在医疗保健中的作用不断扩大,人们越来越意识到AI的潜在陷阱以及需要指导来避免这些陷阱。
    目的:为开发外科培训课程的狭义AI应用提供伦理指导。我们定义了在手术培训中开发AI驱动应用程序的标准化方法,以解决当前公认的在手术数据上使用AI的伦理影响。我们的目标是描述一种基于当前证据的伦理方法,了解人工智能和可用技术,寻求专家委员会的共识。
    方法:该项目分3个阶段进行:(1)成立了一个指导小组,以回顾文献并总结当前的证据。(2)一个更大的专家小组召集并讨论了基于当前证据的AI应用的道德含义。创建了一项调查,与小组成员的输入。(3)第三,使用在线Delphi程序制定指南来确定基于小组的共识结果.30名人工智能实施和/或培训专家,包括临床医生,学者和行业做出了贡献。Delphi过程进行了3轮。第二轮和第三轮调查的补充是根据前几轮的回答和评论制定的。共识意见被定义为≥80%同意。
    结果:所有3轮都有100%的反应。由此制定的指南显示出良好的内部一致性,Cronbachα>0.8.100%的共识是,目前缺乏在机器人手术训练中使用人工智能的指导。在多个领域达成共识,其中:1.数据保护和隐私;2。重复性和透明度;3.预测分析;4.固有偏见;5.最有可能从AI中受益的培训领域。
    结论:使用德尔菲方法,我们在专家之间达成了国际共识,以开发和达成内容验证,以指导AI在外科培训中的伦理影响。为在手术培训中推出狭窄的AI应用程序提供道德基础。本指南需要进一步验证。
    随着AI在医疗保健中的作用不断扩大,人们越来越意识到AI的潜在陷阱以及需要指导来避免这些陷阱。在本文中,我们为AI在外科培训中的伦理意义提供指导。
    BACKGROUND: As the role of AI in healthcare continues to expand there is increasing awareness of the potential pitfalls of AI and the need for guidance to avoid them.
    OBJECTIVE: To provide ethical guidance on developing narrow AI applications for surgical training curricula. We define standardised approaches to developing AI driven applications in surgical training that address current recognised ethical implications of utilising AI on surgical data. We aim to describe an ethical approach based on the current evidence, understanding of AI and available technologies, by seeking consensus from an expert committee.
    METHODS: The project was carried out in 3 phases: (1) A steering group was formed to review the literature and summarize current evidence. (2) A larger expert panel convened and discussed the ethical implications of AI application based on the current evidence. A survey was created, with input from panel members. (3) Thirdly, panel-based consensus findings were determined using an online Delphi process to formulate guidance. 30 experts in AI implementation and/or training including clinicians, academics and industry contributed. The Delphi process underwent 3 rounds. Additions to the second and third-round surveys were formulated based on the answers and comments from previous rounds. Consensus opinion was defined as ≥ 80% agreement.
    RESULTS: There was 100% response from all 3 rounds. The resulting formulated guidance showed good internal consistency, with a Cronbach alpha of >0.8. There was 100% consensus that there is currently a lack of guidance on the utilisation of AI in the setting of robotic surgical training. Consensus was reached in multiple areas, including: 1. Data protection and privacy; 2. Reproducibility and transparency; 3. Predictive analytics; 4. Inherent biases; 5. Areas of training most likely to benefit from AI.
    CONCLUSIONS: Using the Delphi methodology, we achieved international consensus among experts to develop and reach content validation for guidance on ethical implications of AI in surgical training. Providing an ethical foundation for launching narrow AI applications in surgical training. This guidance will require further validation.
    UNASSIGNED: As the role of AI in healthcare continues to expand there is increasing awareness of the potential pitfalls of AI and the need for guidance to avoid them.In this paper we provide guidance on ethical implications of AI in surgical training.
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