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中华临床医师杂志(电子版) ›› 2024, Vol. 18 ›› Issue (11) : 973 -979. doi: 10.3877/cma.j.issn.1674-0785.2024.11.001

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医学成像和放射治疗中的AI 治理审查框架
范文文1,2, 范晓娟3, 白桦2, 张红梅1, 王洁2,()   
  1. 1.100021 北京,国家癌症中心/国家肿瘤临床医学研究中心/中国医学科学院北京协和医学院肿瘤医院影像诊断科
    2.100021 北京,国家癌症中心/国家肿瘤临床医学研究中心/中国医学科学院北京协和医学院肿瘤医院 分子肿瘤学国家重点实验室 AMS 肺癌转化研究重点实验室 肿瘤内科
    3.271000 山东泰安,山东农业大学公共管理学院/泰山法治研究院
  • 收稿日期:2024-08-21 出版日期:2024-11-15
  • 通信作者: 王洁

Artificial intelligence governance review framework for medical imaging and radiotherapy

Wenwen Fan1,2, Xiaojuan Fan3, Hua Bai2, Hongmei Zhang1, Jie Wang2,()   

  1. 1.Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
    2.State Key Laboratory of Molecular Oncology, AMS Key Laboratory of Translational Research on Lung Cancer, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
    3.College of Public Administration, Shandong Agricultural University, Taian 271018, China
  • Received:2024-08-21 Published:2024-11-15
  • Corresponding author: Jie Wang
引用本文:

范文文, 范晓娟, 白桦, 张红梅, 王洁. 医学成像和放射治疗中的AI 治理审查框架[J/OL]. 中华临床医师杂志(电子版), 2024, 18(11): 973-979.

Wenwen Fan, Xiaojuan Fan, Hua Bai, Hongmei Zhang, Jie Wang. Artificial intelligence governance review framework for medical imaging and radiotherapy[J/OL]. Chinese Journal of Clinicians(Electronic Edition), 2024, 18(11): 973-979.

医学成像是最早采用人工智能(AI)技术的学科之一。目前,AI/ML(机器学习)模型已经开始用于辅助影像诊断与治疗。然而,基于AI 驱动的广泛临床应用,仍需要在准确可信任的技术应用与数据隐私保护为代表的法律伦理中寻找一种创新基础。在医学成像与放射领域,AI 治理框架构建需求呈指数级增长。本文基于实用性基本伦理原则,同时考虑到AI 模型的长短期验证与评估程序,提出一个实用治理框架,旨在引导医学成像与放射领域的AI 应用。

Medical imaging is one of the earliest disciplines to adopt artificial intelligence (AI) technology. Currently, AI/ML (machine learning) models are being used to assist in imaging diagnosis and treatment. However, the widespread clinical application of AI necessitates finding an innovative foundation that balances reliable, trustworthy technology with legal and ethical considerations such as data privacy protection. The demand for constructing AI governance frameworks in the field of medical imaging and radiology is growing exponentially. This paper proposes a practical governance framework based on fundamental ethical principles, considering both short-term and long-term validation and evaluation procedures of AI models, with an aim to guide AI applications in the field of medical imaging and radiology.

图1 代表国家和组织医学成像与放射治理实践 注:ACR 为美国放射学会;AIMDs 为AI 医学设备;ESR 为欧洲放射学会;COCIR 为欧洲医学成像技术产业协会
图2 AI 医学成像和放射治疗治理框架及审查要素图
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