面向临床医生的人工智能教育。
AI education for clinicians.
作者信息
Schubert Tim, Oosterlinck Tim, Stevens Robert D, Maxwell Patrick H, van der Schaar Mihaela
机构信息
Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, UK.
Medical Faculty, Heidelberg University, Germany.
出版信息
EClinicalMedicine. 2024 Dec 6;79:102968. doi: 10.1016/j.eclinm.2024.102968. eCollection 2025 Jan.
Abstract
Rapid advancements in medical AI necessitate targeted educational initiatives for clinicians to ensure AI tools are safe and used effectively to improve patient outcomes. To support decision-making among stakeholders in medical education, we propose three tiers of medical AI expertise and outline the challenges for medical education at different educational stages. Additionally, we offer recommendations and examples, encouraging stakeholders to adapt and shape curricula for their specific healthcare setting using this framework.
摘要
医学人工智能的快速发展使得有必要为临床医生开展有针对性的教育活动，以确保人工智能工具的安全性，并能有效地用于改善患者治疗效果。为了支持医学教育利益相关者的决策，我们提出了三个层次的医学人工智能专业知识，并概述了不同教育阶段医学教育所面临的挑战。此外，我们还提供了建议和示例，鼓励利益相关者使用这一框架，针对其特定的医疗环境调整和制定课程。
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