一切都是以人工智能的名义:关于Linardon的评论 (2025)
Pia Burger1,2,3, Sreejita Ghosh4
1GGz Eindhoven, Eindhoven, the Netherlands.
The International journal of eating disorders
|April 15, 2025
概括
医疗保健中的人工智能 (AI) 通常被误解,其能力和感知之间存在差距. 负责任的整合需要理解人工智能.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能在医学中的应用
- 临床决策支持 临床决策支持
背景情况:
- 人工智能 (AI) 快速融入医疗保健环境正在超越患者和临床医生对其真正能力的理解.
- 一个常见的误解是将人工智能完全等同于大型语言模型,忽视了医疗保健中的其他关键人工智能应用.
- 人们担心AI的"黑子"性质,延续偏见的可能性,以及过度依赖它的决定.
研究的目的:
- 要突出人工智能的实际能力与其在医疗保健中的感知作用之间的差异.
- 讨论AI在临床实践中的负责任实施的关键考虑因素.
- 区分各种AI应用,包括行政自动化,临床决策和面向患者的AI.
主要方法:
- 这是一个评论,讨论现有的研究和专家对医疗保健中的AI的意见.
- 对人工智能的"黑盒子"性质和潜在偏见的影响进行分析.
- 检查在临床背景下不同类型的AI应用之间的区别.
主要成果:
- 量化人工智能模型在临床决策任务中表现优于大型语言模型.
- 设计不良的AI可能会成为麻烦或提供错误信息,而设计良好的AI可以赋予患者权力.
- 人工智能集成需要对准确性,可靠性,公平性和现实世界的可用性进行验证.
结论:
- 对人工智能的能力和局限性的细微了解对于其有效地融入医疗保健至关重要.
- 人工智能应该增强,而不是取代临床判断,并提供明确的问责制框架.
- 在医疗保健中负责任的AI实施需要深思熟虑地整合到工作流程和严格的验证中.
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