Brady Adrian P, Allen Bibb, Chong Jaron, Kotter Elmar, Kottler Nina, Mongan John, Oakden-Rayner Lauren, Pinto Dos Santos Daniel, Tang An, Wald Christoph, Slavotinek John
University College Cork, Cork, Ireland.
Department of Radiology, Grandview Medical Center, Birmingham, Alabama, USA.
J Med Imaging Radiat Oncol. 2024 Feb;68(1):7-26. doi: 10.1111/1754-9485.13612. Epub 2024 Jan 23.
Artificial Intelligence (AI) carries the potential for unprecedented disruption in radiology, with possible positive and negative consequences. The integration of AI in radiology holds the potential to revolutionize healthcare practices by advancing diagnosis, quantification, and management of multiple medical conditions. Nevertheless, the ever-growing availability of AI tools in radiology highlights an increasing need to critically evaluate claims for its utility and to differentiate safe product offerings from potentially harmful, or fundamentally unhelpful ones. This multi-society paper, presenting the views of Radiology Societies in the USA, Canada, Europe, Australia, and New Zealand, defines the potential practical problems and ethical issues surrounding the incorporation of AI into radiological practice. In addition to delineating the main points of concern that developers, regulators, and purchasers of AI tools should consider prior to their introduction into clinical practice, this statement also suggests methods to monitor their stability and safety in clinical use, and their suitability for possible autonomous function. This statement is intended to serve as a useful summary of the practical issues which should be considered by all parties involved in the development of radiology AI resources, and their implementation as clinical tools.
人工智能(AI)有可能给放射学带来前所未有的变革,带来可能的积极和消极后果。人工智能在放射学中的整合有潜力通过推进多种医疗状况的诊断、量化和管理来彻底改变医疗实践。然而,放射学中人工智能工具的日益普及凸显出越来越有必要严格评估其效用主张,并区分安全的产品与潜在有害或根本无用的产品。这篇多学会论文展示了美国、加拿大、欧洲、澳大利亚和新西兰放射学会的观点,界定了将人工智能纳入放射学实践所涉及的潜在实际问题和伦理问题。除了阐述人工智能工具的开发者、监管者和购买者在将其引入临床实践之前应考虑的主要关注点外,本声明还提出了监测其在临床使用中的稳定性和安全性以及其对可能的自主功能的适用性的方法。本声明旨在作为一份有用的总结,供参与放射学人工智能资源开发及其作为临床工具实施的所有各方考虑实际问题。