未来医疗评估:在人工智能时代评估协作智能
Yanyi Wu1,2
1School of Public Affairs, Zhejiang University, Hangzhou, China.
概括
医学中的人工智能 (AI) 需要新的技能. 协作智能 (CI) 专注于人-人工智能团队,评估他们合并使用人工智能洞察力的能力,以道德和有效的方式为更好的患者护理.
科学领域:
- 医学教育 医学教育
- 人工智能的人工智能
- 临床实践 临床实践
背景情况:
- 传统的医学教育很难评估人类与人工智能的协作能力.
- 现有的AI框架往往忽视了有效团队合作所需的协同技能.
- 人工智能融入医疗保健需要新的培训和评估方法.
研究的目的:
- 介绍和定义协作智能 (CI) 作为一个以人-AI团队为中心的构造.
- 概述CI的5个核心组成部分:批判性评估,综合,判断,伦理和相互作用.
- 为CI提出一个新的,基于能力的评估框架.
主要方法:
- 定义的协作智能 (CI) 和其核心组件.
- 开发了一个四阶段能力螺旋 (从新手到专家) 评估模型.
- 将各种评估方法 (模拟,工作场所评估) 映射到螺旋上的CI组件上.
主要成果:
- CI被定义为团队评估,整合和根据AI见解采取行动的能力.
- 一个能力螺旋模型取代了CI评估的传统培训阶段.
- 拟议的框架系统地评估不同专业水平的CI.
结论:
- 重新设计医疗评估以测量CI对于医生准备工作至关重要.
- 有效的CI测量确保医生可以利用AI,同时保持医学人文主义.
- 这种方法对于人工智能时代的安全,公平的医疗保健至关重要.
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