辐射瘤学在十字路口:人工智能的兴起和管理意想不到的
1Department of Radiation Oncology, WellSpan Health, Chambersburg, Pennsylvania, USA.
Journal of applied clinical medical physics
|February 18, 2025
概括
辐射瘤学中的人工智能 (AI) 提高了效率,但引入了复杂性. 提出了一个以人为中心的决策的高可靠性组织 (HRO) 框架,以管理不可预测的AI事件并确保患者安全.
科学领域:
- 医学物理 医学物理
- 辐射瘤学 辐射瘤学
- 人工智能的人工智能
背景情况:
- 人工智能 (AI) 在放射瘤学中的整合提高了临床工作流程,效率和患者安全.
- 然而,人工智能实施带来了更大的复杂性和不可预见事件的可能性.
研究的目的:
- 提出一个框架来管理实时,AI驱动的辐射瘤学中不可预测的事件.
- 为了提高患者的安全,在不断增加的AI复杂性.
主要方法:
- 基于高可靠性组织 (HRO) 原则的框架.
- 强调主动风险评估和适应性团队合作.
- 整合以人为中心的决策,认知多样性,心理安全和情绪智能.
主要成果:
- 拟议的HRO框架有助于管理与AI相关的意外事件.
- 以人为中心的决策是导航AI复杂性的核心.
- 通过多元化的团队促进集体智能增强适应性和安全性.
结论:
- 实施HRO框架对于在放射性瘤学中安全整合AI至关重要.
- 积极的风险管理和适应性的团队合作是解决人工智能驱动的复杂性的关键.
- 优先考虑认知多样性和心理安全等人类因素,确保在AI增强的环境中提供强大的患者护理.
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