人工智能应该真正支持临床推理和决策,以弥合翻译差距
Kacper Sokol1, James Fackler2,3, Julia E Vogt4
1Department of Computer Science, ETH Zurich, Zurich, Switzerland. kacper.sokol@inf.ethz.ch.
NPJ digital medicine
|June 10, 2025
概括
医学中的人工智能面临着由于翻译差距的挑战. 提出了一种新的社会技术方法,以更好地支持医生.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 社会技术系统 社会技术系统
背景情况:
- 人工智能 (AI) 对彻底改变医疗实践具有重大前景.
- 然而,由于人工智能开发和临床实施之间存在持续的翻译差距,其广泛采用受到阻碍.
- 目前以技术为中心的AI方法往往无法无地融入临床工作流程.
研究的目的:
- 为了解决当前AI在医学中的局限性.
- 为人工智能驱动的医疗支持工具提出一个新的概念.
- 提高AI在临床环境中的实际实用性和现实影响.
主要方法:
- 批评医学中普遍存在的以技术为中心的AI开发范式.
- 介绍人工智能支持工具的社会技术概念化.
- 专注于补充临床医生的认知和认识过程.
主要成果:
- 确定以技术为中心的方法是AI在医学采用的关键障碍.
- 为设计人工智能工具提出了一个社会技术框架.
- 从基准表现转向现实世界的临床影响.
结论:
- 社会技术视角对于弥合医学AI的翻译差距至关重要.
- 人工智能工具应该被设计为增强,而不是取代临床医生的决策能力.
- 优先考虑现实世界的实用性,而不是抽象的性能指标,将加速人工智能的有益整合到医疗保健中.
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