关于ACR实践认证放射学人工智能的路线图
David B Larson1, Mythreyi Bhargavan-Chatfield2, Michael Tilkin3
1Director of the AI Development and Evaluation Lab, Department of Radiology, Stanford University School of Medicine, Stanford, California; Chair, ACR Commission on Quality and Safety; Member of the ACR Board of Chancellors.
Journal of the American College of Radiology : JACR
|March 9, 2025
概括
美国放射学学院 (ACR) 正在制定放射学人工智能 (AI) 认证计划,以确保安全有效的临床使用. 这个倡议针对的是人工智能.
科学领域:
- 放射学 放射学是一门学科.
- 人工智能的人工智能
- 医疗保健质量管理 医疗保健质量管理
背景情况:
- 人工智能 (AI) 在现实世界放射学环境中的表现往往偏离市场前测试.
- 强大的质量管理 (QM) 计划对于安全的AI在医疗保健中的实施至关重要.
- 目前的ACR认证过程不包括放射学AI.
研究的目的:
- 概述建立一个ACR认证计划的计划,用于AI在放射学.
- 确保人工智能安全有效地融入临床放射学实践.
- 解决对人工智能工具标准化质量评估的需求.
主要方法:
- 利用现有的ACR认证框架,包括实践参数和技术标准.
- 建立ACR认可的医疗保健-AI中心 (ARCH-AI) 作为前身计划.
- 从ARCH-AI参与者那里收集有关治理,模型选择,测试和监测的见解.
主要成果:
- 该ARCH-AI计划是通往正式AI认证的基础步骤.
- 来自ARCH-AI的见解将为制定全面的认证标准提供信息.
- 放射学AI的正式ACR认证预计将在2027年春季完成.
结论:
- 对放射学AI的ACR认证对于保持高标准的护理至关重要.
- 拟议的计划旨在提高患者安全,并优化AI的临床效益.
- 利益相关者之间的持续对话将引导人工智能认证的成功实施.
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