Discipline of Medical Imaging and Radiation Therapy, University College Cork, Cork, Ireland.
Division of Midwifery & Radiography, City, University of London, London, United Kingdom.
Br J Radiol. 2023 Dec;96(1152):20221157. doi: 10.1259/bjr.20221157. Epub 2023 Oct 3.
Technological advancements in computer science have started to bring artificial intelligence (AI) from the bench closer to the bedside. While there is still lots to do and improve, AI models in medical imaging and radiotherapy are rapidly being developed and increasingly deployed in clinical practice. At the same time, AI governance frameworks are still under development. Clinical practitioners involved with procuring, deploying, and adopting AI tools in the UK should be well-informed about these AI governance frameworks. This scoping review aimed to map out available literature on AI governance in the UK, focusing on medical imaging and radiotherapy. Searches were performed on Google Scholar, Pubmed, and the Cochrane Library, between June and July 2022. Of 4225 initially identified sources, 35 were finally included in this review. A comprehensive conceptual AI governance framework was proposed, guided by the need for rigorous AI validation and evaluation procedures, the accreditation rules and standards, and the fundamental ethical principles of AI. Fairness, transparency, trustworthiness, and explainability should be drivers of all AI models deployed in clinical practice. Appropriate staff education is also mandatory to ensure AI's safe and responsible use. Multidisciplinary teams under robust leadership will facilitate AI adoption, and it is crucial to involve patients, the public, and practitioners in decision-making. Collaborative research should be encouraged to enhance and promote innovation, while caution should be paid to the ongoing auditing of AI tools to ensure safety and clinical effectiveness.
计算机科学领域的技术进步已经开始将人工智能(AI)从实验室带到床边。虽然还有很多工作要做和改进,但医学影像和放射治疗中的 AI 模型正在迅速开发,并越来越多地应用于临床实践。与此同时,人工智能治理框架仍在制定中。在英国,参与采购、部署和采用人工智能工具的临床医生应该充分了解这些人工智能治理框架。本范围综述旨在绘制英国人工智能治理领域的现有文献图谱,重点关注医学影像和放射治疗。2022 年 6 月至 7 月,在谷歌学术、PubMed 和 Cochrane 图书馆进行了搜索。在最初确定的 4225 个来源中,最终有 35 个被纳入本综述。在严格的人工智能验证和评估程序、认证规则和标准以及人工智能的基本伦理原则的指导下,提出了一个全面的概念性人工智能治理框架。公平、透明、可信赖和可解释性应该是所有部署在临床实践中的人工智能模型的驱动因素。还必须对员工进行适当的教育,以确保人工智能的安全和负责任使用。在强大领导力下的多学科团队将促进人工智能的采用,必须让患者、公众和从业者参与决策。应该鼓励合作研究以促进创新,同时要注意对人工智能工具的持续审计,以确保其安全性和临床有效性。